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Peer Review in Computer Science: good, bad & broken

Discuss everything about peer review in computer science research: its successes, failures, and the challenges in between.

This category can be followed from the open social web via the handle cs-peer-review-general@cspaper.org:443

73 Topics 243 Posts

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  • Discuss peer review challenges in AI/ML research — submission, review quality, bias, and decision appeals at ICLR, ICML, NeurIPS, AAAI, IJCAI, AISTATS and COLT.

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    rootR
    Saw this picture, pretty fun [image: 1750978469485-screenshot-2025-06-27-at-00.54.14.png]
  • Discuss peer review challenges, submission experiences, decision fairness, reviewer quality, and biases at CVPR, ICCV, ECCV, VR, SIGGRAPH, EUROGRAPHICS, ICRA, IROS, RSS etc.

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    rootR
    Shocking Cases, Reviewer Rants, Score Dramas, and the True Face of CV Top-tier Peer Review! “Just got a small heart attack reading the title.” — u/Intrepid-Essay-3283, Reddit [image: giphy.gif] Introduction: ICCV 2025 — Not Just Another Year ICCV 2025 might have broken submission records (11,239 papers! 🤯), but what really set this year apart was the open outpouring of review experiences, drama, and critique across communities like Zhihu and Reddit. If you think peer review is just technical feedback, think again. This year, it was a social experiment in bias, randomness, AI-detection accusations, and — sometimes — rare acts of fairness. Below, we dissect dozens of real cases reported by the community. Expect everything: miracle accepts, heartbreak rejections, reviewer bias, AC heroics, AI accusations, desk rejects, and score manipulation. Plus, we bring you the ultimate summary table — all real, all raw. The Hall of Fame: ICCV 2025 Real Review Cases Here’s a complete table of every community case reported above. Each row is a real story. Find your favorite drama! # Initial Score Final Score Rebuttal Effect Decision Reviewer/AC Notes / Notable Points Source/Comment 1 4/4/2 5/4/4 +1, +2 Accept AC sided with authors after strong rebuttal Reddit, ElPelana 2 5/4/4 6/5/4 +1, +1 Reject Meta-review agreed novelty, but blamed single baseline & "misleading" boldface Reddit, Sufficient_Ad_4885 3 5/4/4 5/4/4 None Reject Several strong scores, still rejected Reddit, kjunhot 4 5/5/3 6/5/4 +1, +2 Accept "Should be good" - optimism confirmed! Reddit, Friendly-Angle-5367 5 4/4/4 4/4/4 None Accept "Accept with scores of 4/4/4/4 lol" Reddit, ParticularWork8424 6 5/5/4 6/5/4 +1 Accept No info on spotlight/talk/poster Reddit, Friendly-Angle-5367 7 4/3/2 4/3/3 +1 Accept AC "saved" the paper! Reddit, megaton00 8 5/5/4 6/5/4 +1 Accept (same as #6, poster/talk unknown) Reddit, Virtual_Plum121 9 5/3/2 4/4/2 mixed Reject Rebuttal didn't save it, "incrementality" issue Reddit, realogog 10 5/4/3 - - Accept Community optimism for "5-4-3 is achievable" Reddit, felolorocher 11 4/4/2 4/4/3 +1 Accept AC fought for the paper, luck matters! Reddit, Few_Refrigerator8308 12 4/3/4 4/4/5 +1 Accept Lucky with AC Reddit, Ok-Internet-196 13 5/3/3 4/3/3 -1 (from 5 to 4) Reject Reviewer simply wrote "I read the rebuttals and updated my score." Reddit, chethankodase 14 5/4/1 6/6/1 +1/+2 Reject "The reviewer had a strong personal bias, but the ACs were not convinced" Reddit, ted91512 15 5/3/3 6/5/4 +1/+2 Accept "Accepted, happy ending" Reddit, ridingabuffalo58 16 6/5/4 6/6/4 +1 Accept "Accepted but not sure if poster/oral" Reddit, InstantBuffoonery 17 6/3/2 - None Reject "Strong accept signals" still not enough Reddit, impatiens-capensis 18 5/5/2 5/5/3 +1 Accept "Reject was against the principle of our work" Reddit, SantaSoul 19 6/4/4 6/6/4 +2 Accept Community support for strong scores Reddit, curious_mortal 20 4/4/2 6/4/2 +2 Accept AC considered report about reviewer bias Reddit, DuranRafid 21 3/4/6 3/4/6 None Reject BR reviewer didn't submit final, AC rejected Reddit, Fluff269 22 355 555 +2 Accept "Any chance for oral?" Reddit, Beginning-Youth-6369 23 5/3/2 - - TBD "Had a good rebuttal, let's see!" Reddit, temporal_guy 24 4/3/4 - - TBD "Waiting for good results!" Reddit, Ok-Internet-196 25 5/5/4 5/5/4 None Accept "555 we fn did it boys" Reddit, lifex_ 26 633 554 - Accept "Here we go Hawaii♡" Reddit, DriveOdd5983 27 554 555 +1 Accept "Many thanks to AC" Reddit, GuessAIDoesTheTrick 28 345 545 +2 Accept "My first Accept!" Reddit, Fantastic_Bedroom170 29 4/4/2 232 -2, -2 Reject "Reviewers praised the paper, but still rejected" Reddit, upthread 30 5/4/4 5/4/4 None Reject "Another 5/4/4 reject here!" Reddit, kjunhot 31 432 432 None TBD "432 with hope" Zhihu, 泡泡鱼 32 444 444 None Accept "3 borderline accepts, got in!" Zhihu, 小月 33 553 555 +2 Accept "5-score reviewer roasted the 3-score reviewer" Zhihu, Ealice 34 554 555 +1 Accept "Highlight downgraded to poster, but happy" Zhihu, Frank 35 135 245 +1/+2 Reject "Met a 'bad guy' reviewer" Zhihu, Frank 36 235 445 +2 Accept "Congrats co-authors!" Zhihu, Frank 37 432 432 None Accept "AC appreciated explanation, saved the paper" Zhihu, Feng Qiao 38 442 543 +1/+1 Accept "After all, got in!" Zhihu, 结弦 39 441 441 None TBD "One reviewer 'writing randomly'" Zhihu, ppphhhttt 40 4/4/3/2 - - TBD "Asked to use more datasets for generalization" Zhihu, 随机 41 446 (443) - - TBD "Everyone changed scores last two days" Zhihu, 877129391241 42 553 553 None Accept "Thanks AC for acceptance" Zhihu, Ealice 43 4/4/3/2 - - Accept "First-time submission, fair attack points" Zhihu, 张读白 44 4/4/4 4/4/4 None Accept "Confident, hoping for luck" Zhihu, hellobug 45 5541 - - TBD "Accused of copying concurrent work" Zhihu, 凪·云抹烟霞 46 554 555 +1 Accept "Poster, but AC downgraded highlight" Zhihu, Frank 47 6/3/2 - None Reject High initial, still rejected Reddit, impatiens-capensis 48 432 432 None Accept "Average final 4, some hope" Zhihu, 泡泡鱼 49 563 564 +1 Accept "Grateful to AC!" Zhihu, 夏影 50 6/5/4 6/6/4 +1 Accept "Accepted, not sure if poster or oral" Reddit, InstantBuffoonery NOTE: This is NOT an exhaustive list of all ICCV 2025 papers, but every real individual case reported in the Zhihu and Reddit community discussions included above. Many entries were “update pending” at posting — when the author didn’t share the final result, marked as TBD. Many papers changed hands between accept/reject on details like one reviewer not updating, AC/Meta reviewer overrides, “bad guy”/mean reviewers, and luck with batch cutoff. 🧠 ICCV 2025 Review Insights: What Did We Learn? 1. Luck Matters — Sometimes More Than Merit Multiple papers with 5/5/3 or even 6/5/4 were rejected. Others with one weak reject (2) got in — sometimes only because the AC “fought for it.” "Getting lucky with the reviewers is almost as important as the quality of the paper itself." (Reddit) 2. Reviewer Quality Is All Over the Place Dozens reported short, generic, or careless reviews — sometimes 1-2 lines with major negative impact. Multiple people accused reviewers of being AI-generated (GPT/Claude/etc.) — several ran AI detectors and reported >90% “AI-written.” Desk rejects were sometimes triggered by reviewer irresponsibility (ICCV officially desk-rejected 29 papers for "irresponsible" reviewers). 3. Rebuttal Can Save You… Sometimes Many cases where good rebuttals led to score increases and acceptance. But also numerous stories where reviewers didn’t update, or even lowered scores post-rebuttal without clear reason. 4. Meta-Reviewers & ACs Wield Real Power Several stories where ACs overruled reviewers (for both acceptance and rejection). Meta-reviewer “mistakes” (e.g., recommend accept but click reject) — some authors appealed and got the result changed. 5. System Flaws and Community Frustrations Complaints about the “review lottery”, irresponsible/underqualified reviewers, ACs ignoring rebuttal, and unfixable errors. Many hope for peer review reform: more double-blind accountability, reviewer rating, and even rewards for good reviewing (see this arXiv paper proposing reform). Community Quotes & Highlights "Now I believe in luck, not just science." — Anonymous "Desk reject just before notification, it's a heartbreaker." — 877129391241, Zhihu "I got 555, we did it boys." — lifex, Reddit "Three ACs gave Accept, but it was still rejected — I have no words." — 寄寄子, Zhihu "Training loss increases inference time — is this GPT reviewing?" — Knight, Zhihu "Meta-review: Accept. Final Decision: Reject. Reached out, they fixed it." — fall22_cs_throwaway, Reddit Final Thoughts: Is ICCV Peer Review Broken? ICCV 2025 gave us a microcosm of everything good and bad about large-scale peer review: scientific excellence, reviewer burnout, human bias, reviewer heroism, and plenty of randomness. Takeaways: Prepare your best work, but steel yourself for randomness. Test early on https://review.cspaper.org before and after submission to help build reasonable expectation Craft a strong, detailed rebuttal — sometimes it works miracles. If you sense real injustice, appeal or contact your AC, but don’t count on it. Above all: Don’t take a single decision as a final judgment of your science, your skill, or your future. Join the Conversation! What was YOUR ICCV 2025 review experience? Did you spot AI-generated reviews? Did a miracle rebuttal save your work? Is the peer review crisis fixable, or are we doomed to reviewer roulette forever? “Always hoping for the best! But worse case scenario, one can go for a Workshop with a Proceedings Track!” — Reddit [image: peerreview-nickkim.jpg] Let’s keep pushing for better science — and a better system. If you find this article helpful, insightful, or just painfully relatable, upvote and share with your fellow researchers. The struggle is real, and you are not alone!
  • Discuss peer review, submission experiences, and decision challenges for NLP research at ACL, EMNLP, NAACL, and COLING.

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    JoanneJ
    [image: 1748542849019-5025817c-fdc3-47eb-8124-862024badd04-image.png] In a historic milestone for artificial intelligence and scientific research, Zochi, an AI research agent created by Intology AI, has become the first artificial system to independently author and pass peer review at the main proceedings of the Association for Computational Linguistics (ACL), the world’s most prestigious venue for natural-language-processing (NLP) research. A First in Scientific Publishing: Clearing the A* Bar Zochi’s paper, “Tempest: Automatic Multi-Turn Jailbreaking of Large Language Models with Tree Search,” was accepted to ACL 2025, a conference with an acceptance rate of roughly 20% often considered more selective than NeurIPS or ICML. In contrast, earlier AI-generated papers only reached workshop tracks, where acceptance rates hover around 60% to 70%. This achievement signals the arrival of AI systems as independent scientific contributors, capable of producing research that competes with the work of top human scholars. A New Breed of Researcher: Autonomous Scientific Discovery Zochi is far more than another large language model. It is an autonomous scientific agent that can: Survey literature and generate hypotheses Design and run experiments with rigorous controls Analyze results and iterate on methodology Write the final manuscript, leaving humans to handle only formatting tweaks and figure polishing By automating the entire research pipeline, Zochi can deliver validated scientific contributions in days rather than the months or years typical of human-led projects. “Tempest”: A Paper That Raises Safety Alarms The accepted paper targets a critical AI-safety problem: multiturn jailbreak attacks that coax language models into violating policy via extended dialogue. Tempest employs a tree search strategy that explores multiple conversational branches in parallel and adapts in real time to partial-compliance signals. The results: 100% success against GPT-3.5-Turbo 97% success against GPT-4 Fewer queries than competing methods “This work shows how small policy concessions can snowball into critical violations, offering both a wake-up call and a blueprint for stronger defenses,” notes the paper’s meta-review. Zochi’s submission ranked in the top 8.2 percent of all ACL papers, earning a final meta-review score of 4/5 for exceptional merit and novelty. Ethical Implications and Responsible Disclosure Intology stresses that, despite Zochi’s autonomy, humans remain accountable. They recommend listing AI systems in the Acknowledgements, not as co-authors, to maintain transparency around authorship. All experimental results were internally verified, and the rebuttal to reviewers was written by humans to ensure compliance with academic standards. What’s Next: Zochi Goes Public After its ACL breakthrough, Intology will launch a public beta of Zochi: Phase 1: Domain agnostic research copilot, helping researchers find ideas, craft proposals, and design experiments Phase 2: Gradual rollout of end-to-end autonomous research capabilities across scientific disciplines This roadmap heralds a new era of human AI collaboration in discovery. With more papers being written by AI, isn’t it time to let AI help review them too? Perhaps it’s time to fight fire with fire. [image: 1748542689718-4cb14c31-b76d-4705-bda3-a9fd60273f4c-image.png] Further Reading 🧠 Read the paper on arXiv Intology’s announcement blog Discussion on X
  • SIGKDD, SIGMOD, ICDE, CIKM, WSDM, VLDB, ICDM and PODS

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    rootR
    The early bird deadline is June 18th! Register on or before the deadline to receive discounted rates for KDD 2025!
  • ICSE, OSDI, SOSP, POPL, PLDI, FSE/ESEC, ISSTA, OOPSLA and ASE

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    rootR
    It seems CCF is revising the list again: https://www.ccf.org.cn/Academic_Evaluation/By_category/2025-05-09/841985.shtml
  • HCI, CSCW, UniComp, UIST, EuroVis and IEEE VIS

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    JoanneJ
    [image: 1750758497155-fa715fd6-ed5a-44be-8c8d-84f1645fac47-image.png] CHI remains the flagship venue in the HCI field. It draws researchers from diverse disciplines, consistently puts humans at the center, and amplifies research impact through high quality papers, compelling keynotes, and extensive doctoral consortia. Yet CHI isn’t the entirety of the HCI landscape. It’s just the heart of a much broader ecosystem. Here’s a quick-look field guide Six flagship international HCI conferences Acronym What makes it shine Ideal authors Home page Photo UIST Hardware & novel interface tech; demo heavy culture System / device researchers https://uist.acm.org/2025/ [image: 1750757345992-d6b2b397-f753-40fd-b2b7-2410ed6556b9-image.png] SIGGRAPH Graphics core plus dazzling VR/AR & 3-D interaction showcases Graphics, visual interaction & art-tech hybrids https://www.siggraph.org/ [image: 1750757560460-6657b0b8-06d3-4c27-bc03-6f449a03b7c2-image.png] MobileHCI Interaction in mobile, wearable & ubiquitous contexts Ubicomp oriented, real world applications https://mobilehci.acm.org/2024/ [image: 1750757628685-22f47458-89b5-4f9c-8718-ee89249c1e49-image.png] CSCW Collaboration, remote work & social media at scale Socio-technical & social computing teams https://cscw.acm.org/2025/ [image: 1750757750339-ea17f345-83b9-47f3-af41-6623bdf45eab-image.png] DIS Creative, cultural & critical interaction design UX, speculative & experience driven scholars https://dis.acm.org/2025/ [image: 1750757796645-b1212781-047f-4afc-89a4-e07691e25225-image.png] CHI Broadest scope, human centred ethos, highest brand value Any HCI sub field https://chi2026.acm.org/ [image: 1750757827999-a2b6e621-cbbb-428c-929c-97d243165d19-image.png] Four high-impact HCI journals Journal Focus Good for Home page ACM TOCHI Major theoretical / methodological breakthroughs Large, mature studies needing depth https://dl.acm.org/journal/tochi IJHCS <br>(International Journal of Human-Computer Studies) Cognition → innovation → UX Theory blended with applications https://www.sciencedirect.com/journal/international-journal-of-human-computer-studies CHB <br>(Computers in Human Behavior) Psychological & behavioural angles on HCI Quant-heavy user studies & surveys https://www.sciencedirect.com/journal/computers-in-human-behavior IJHCI <br>(International Journal of Human-Computer Interaction) Cognitive, creative, health-related themes Breadth from conceptual to applied work https://www.tandfonline.com/journals/hihc20 ️ Conference vs. journal: choosing the right vehicle Conferences prize speed: decision to publication can be mere months, papers are concise, and novelty is king. Journals prize depth: multiple revision rounds, no strict length cap, and a focus on long term influence. When a conference is smarter 🧪 Fresh prototypes or phenomena that need rapid peer feedback Face-to-face networking with collaborators and recruiters ️ Time-sensitive results where a decision within months matters 🧭 When a journal pays off Data and theory fully polished and deserving full exposition Citation slow burn for tenure or promotion dossiers Ready for iterative reviews to reach an authoritative version Take-away If CHI is the main stage , UIST, SIGGRAPH, MobileHCI, CSCW & DIS are the satellite arenas ️; TOCHI, IJHCS, CHB & IJHCI serve as deep archives . Match your study’s maturity, urgency and career goals to the venue, follow the links above, and—once you’ve dropped in those shiny images—let the best audience discover your work. Happy submitting!
  • Anything around peer review for conferences such as SIGIR, WWW, ICMR, ICME, ECIR, ICASSP and ACM MM.

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    riverR
    Recently, someone surfaced (again) a method to query the decision status of a paper submission before the official release for ICME 2025. By sending requests to a specific API (https://cmt3.research.microsoft.com/api/odata/ICME2025/Submissions(Your_paper_id)) endpoint in the CMT system, one can see the submission status via a StatusId field, where 1 means pending, 2 indicates acceptance, and 3 indicates rejection. This trick is not limited to ICME 2025. It appears that the same method can be applied to several other conferences, including: IJCAI, ICME, ICASSP, IJCNN and ICMR. However, it is important to emphasize that using this technique violates the fairness and integrity of the peer-review process. Exploiting such a loophole undermines the confidentiality and impartiality that are essential to academic evaluations. This is a potential breach of academic ethics, and an official fix is needed to prevent abuse. Below is a simplified Python script that demonstrates how this status monitoring might work. Warning: This code is provided solely for educational purposes to illustrate the vulnerability. It should not be used to bypass proper review procedures. import requests import time import smtplib from email.mime.text import MIMEText from email.header import Header import logging # Configure logging logging.basicConfig( level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s', handlers=[ logging.FileHandler("submission_monitor.log"), logging.StreamHandler() ] ) # List of submission URLs to monitor (replace 'Your_paper_id' accordingly) SUBMISSION_URLS = [ "https://cmt3.research.microsoft.com/api/odata/ICME2025/Submissions(Your_paper_id)", "https://cmt3.research.microsoft.com/api/odata/ICME2025/Submissions(Your_paper_id)" ] # Email configuration (replace with your actual details) EMAIL_CONFIG = { "smtp_server": "smtp.qq.com", "smtp_port": 587, "sender": "your_email@example.com", "password": "your_email_password", "receiver": "recipient@example.com" } def get_status(url): """ Check the submission status from the provided URL. Returns the status ID and a success flag. """ try: headers = { 'User-Agent': 'Mozilla/5.0', 'Accept': 'application/json', 'Referer': 'https://cmt3.research.microsoft.com/ICME2025/', # Insert your cookie here after logging in to CMT 'Cookie': 'your_full_cookie' } response = requests.get(url, headers=headers, timeout=30) if response.status_code == 200: data = response.json() status_id = data.get("StatusId") logging.info(f"URL: {url}, StatusId: {status_id}") return status_id, True else: logging.error(f"Failed request. Status code: {response.status_code} for URL: {url}") return None, False except Exception as e: logging.error(f"Error while checking status for URL: {url} - {e}") return None, False def send_notification(subject, message): """ Send an email notification with the provided subject and message. """ try: msg = MIMEText(message, 'plain', 'utf-8') msg['Subject'] = Header(subject, 'utf-8') msg['From'] = EMAIL_CONFIG["sender"] msg['To'] = EMAIL_CONFIG["receiver"] server = smtplib.SMTP(EMAIL_CONFIG["smtp_server"], EMAIL_CONFIG["smtp_port"]) server.starttls() server.login(EMAIL_CONFIG["sender"], EMAIL_CONFIG["password"]) server.sendmail(EMAIL_CONFIG["sender"], [EMAIL_CONFIG["receiver"]], msg.as_string()) server.quit() logging.info(f"Email sent successfully: {subject}") return True except Exception as e: logging.error(f"Failed to send email: {e}") return False def monitor_submissions(): """ Monitor the status of submissions continuously. """ notified = set() logging.info("Starting submission monitoring...") while True: for url in SUBMISSION_URLS: if url in notified: continue status, success = get_status(url) if success and status is not None and status != 1: email_subject = f"Submission Update: {url}" email_message = f"New StatusId: {status}" if send_notification(email_subject, email_message): notified.add(url) logging.info(f"Notification sent for URL: {url} with StatusId: {status}") if all(url in notified for url in SUBMISSION_URLS): logging.info("All submission statuses updated. Ending monitoring.") break time.sleep(60) # Wait for 60 seconds before checking again if __name__ == "__main__": monitor_submissions() Parting thoughts While the discovery of this loophole may seem like an ingenious workaround, it is fundamentally unethical and a clear violation of the fairness expected in academic peer review. Exploiting such vulnerabilities not only compromises the integrity of the review process but also undermines the trust in scholarly communications. We recommend the CMT system administrators to implement an official fix to close this gap. The academic community should prioritize fairness and the preservation of rigorous, unbiased review standards over any short-term gains that might come from exploiting such flaws.
  • Anything around peer review for conferences such as ISCA, FAST, ASPLOS, EuroSys, HPCA, SIGMETRICS, FPGA and MICRO.

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    rootR
    R.I.P. USENIX ATC ...
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    JoanneJ
    Yeah. Can't wait to see how AAAI 2026 First AI-Assisted Peer Review performs.
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    JoanneJ
    This is not the first time to have "F" word in journal paper, but it's on the most impactful journal. One of the ridiculous paper published was on International Journal of Advanced Computer Technology, originally created by two computer scientists in 2005 as a joke response to spammy academic invitations, with the title: <Get me off Your Fucking Mailing List>. [image: 1748104001215-c78069b7-5d54-427a-8d57-11b24233374d-image.png] [image: 1748103841726-bfa55487-5ecb-428c-9838-b91ab33ef101-image.png] [image: 1748103873929-87fa34a9-e26d-49a3-9781-9c2cd93b654f-image.png] Then, there is an other paper published by Vamplew, Peter tilted: "Get me off Your Fucking Mailing List." in Зборник Матице српске за друштвене науке 154 (2016), abut this. Vamplew has this written in the abstract: "A paper titled “Get me off your fcking mailing list” has been accepted by the International Journal of Advanced Computer Technology. But, as Joseph Stromberg reports for Vox, there’s more going on here than just a hilariously missing-in-action peer-review system – it highlights the bigger problem of predatory journals, which try to get young academics pay to have their work published, and shows just how shonky they are. Despite how fancy the journal sounds, the International Journal of Advanced Computer Technology is actually an open-access publication that spams thousands of scientists every day with the offer of publishing their work – for a price, of course. Back in 2005, US computer scientists David Mazières and Eddie Kohler created this 10-page paper as a joke response they could send to annoying and unwanted conference invitations. As well as the seven-word headline being repeated over and over again, the paper also contained some very helpful flow charts and graphs, [....] [See Figure 1 above!] The PDF went pretty viral in academic circles, and then recently an Australian scientist named Peter Vamplew sent it off to the pain-in-the-ass International Journal of Advanced Computer Technology in the hope that the editors would open it, read it and take him off their fcking list. Instead, Scholarly Open Access reports that they took it as a real submission and said they’d publish it for $150. Apparently the journal even sent the paper to an anonymous reviewer who said it was “excellent”. As Stromberg writes for Vox: “This incident is pretty hilarious. But it’s a sign of a bigger problem in science publishing. This journal is one of many online-only, forprofit operations that take advantage of inexperienced researchers under pressure to publish their work in any outlet that seems superficially legitimate. They’re very different from respected, rigorous journals like Science and Nature that publish much of the research you read about in the news. Most troublingly, the predatory journals don’t conduct peer-review – the process where other scientists in the field evaluate a paper before it’s published.” Not only that, but in this instance the journal didn’t even seem to care that the scientist who submitted it wasn’t actually the one who wrote the article. This isn’t the first time these predatory journals have been caught out, Stromberg reports, but unfortunately it shows that the problem doesn’t seem to be going anywhere anytime soon. Read Stromberg’s excellent full story on the paper and predatory journals over at Vox. And next time we get spammed by unwanted emails, we know what we’ll be sending back."
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    Where do we go from here — through the lens of the CS top-tier conference rules? Many flagship venues have now staked out clear positions. ICML and AAAI, for instance, continue to prohibit any significant LLM-generated text in submissions unless it’s explicitly part of the paper’s experiments (in other words, no undisclosed LLM-written paragraphs). NeurIPS and the ACL family of conferences permit the use of generative AI tools but insist on transparency – authors must openly describe how such tools were used, especially if they influenced the research methodology or content. Meanwhile, ICLR adopts a more permissive stance, allowing AI-assisted writing with only gentle encouragement toward responsible use (there is no formal disclosure requirement beyond not listing an AI as an author). With that in place, what will the next phase could look like? could it be this following? : One disclosure form to rule them all – expect a standard section (akin to ACL’s Responsible NLP Checklist, but applied across venues) where authors tick boxes: what tool was used, what prompt given, at which stage, and what human edits were applied. Built-in AI-trace scanners at submission – Springer Nature’s “Geppetto” tool has shown it’s feasible to detect AI-generated text; conference submission platforms (CMT/OpenReview) might adopt similar detectors to nudge authors towards honesty before reviewers ever see the paper. Fine-grained permission tiers – “grammar-only” AI assistance stays exempt from reporting, but any AI involvement in drafting ideas, claims, or code would trigger a mandatory appendix detailing the prompts used and the post-editing steps taken. Authorship statements 2.0 – we’ll likely keep forbidding LLMs as listed authors, yet author contribution checklists could expand to include items like “AI-verified output,” “dataset curated via AI,” or “AI-assisted experiment design,” acknowledging more nuanced roles of AI in the research. Cross-venue integrity task-forces – program chairs from NeurIPSICMLACL could share a blacklist of repeat violators (much as journals share plagiarism data) and harmonize sanctions across conferences to present a united front on misconduct. Or… will we settle for a loose system, with policies diverging year by year and enforcement struggling to keep pace? Your call: Is the field marching toward transparent, template-driven co-writing with AI, or are we gearing up for the next round of cat-and-mouse?
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    N
    I believe this is not the only case, have seen more of alike.
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  • On the role reproducibility for peer reviews

    reproducibility peer review
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    cqsyfC
    Great points! OpenAI’s new PaperBench shows how tough reproducibility still is in ML. It asked AI agents to replicate 20 ICML 2024 papers from scratch. Even the best model only got 21%, while human PhDs reached 41.4%. [image: 1743714483369-screenshot-2025-04-03-at-23.07.45-resized.png] What stood out is how they worked with authors to define 8,000+ fine-grained tasks for scoring. It shows we need better structure, clearer standards, and possibly LLM-assisted tools (like their JudgeEval) to assess reproducibility at scale. Maybe it’s time to build structured reproducibility checks into peer review, i.e., tools like PaperBench give us a way forward. Checkout the Github: https://github.com/openai/preparedness
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    rootR
    Interesting research that got accepted by EMNLP 2023 findings.
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    lelecaoL
    It is heating up. The scale and tooling for peer review will have to catch up.
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    lelecaoL
    Thanks for sharing these thinking! I totally resonate with your points, especially about incremental research still being valuable. Not every paper can be paradigm-shifting, and recognizing solid, incremental progress helps keep science moving forward. Plus, the emphasis on methodological rigor and ethical considerations is spot-on. Peer review isn’t easy, but clear guidelines like these definitely make the process smoother ...
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    valbucV
    Really interesting thought experiment! Compared to other fields such as medicine, I think it is a very good thing that there are usually no or very low processing feels for getting an article published. This really opens up the research to everyone. Compensating the reviewers would make it difficult to keep the fees low. Plus, the improvements in review quality seem to be rather marginal! What do you thing universities/research departments could do to incentivise better reviews?
  • Improving Peer Review: A Must-See Tutorial

    cvpr 2020 tutorial
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