CSPaper: review sidekick

Love it! seems pretty simple to use! Thanks!

What?! Dataverse picking this moment to bail. Totally feeling your pain.

Impl. based on nr0034je9.zip . Table A: Model Performance on NLP Benchmarks Model SST-2 (Acc) MNLI (Acc) QNLI (Acc) CoLA (Matthews) Avg Score BERT-Base 91.2 84.6 90.1 58.2 81.0 RoBERTa-Base 92.3 87.4 91.8 63.1 83.7 GPT-3 (175B) 94.1 88.9 93.0 66.4 85.6 Our Method 94.8 89.7 93.5 68.9 86.7 Table B: Ablation Study on Model Components (Evaluated on MNLI) Configuration Attention Mechanism Pretraining Corpus MNLI (Acc) Full Model Multi-head Self-Attn Custom + Public 89.7 – w/o Custom Corpus Multi-head Self-Attn Public Only 87.1 – w/o Attention Refinement Block Basic Self-Attn Custom + Public 86.5 – w/o Positional Embeddings Multi-head Self-Attn Custom + Public 85.2 – Random Initialization — — 72.4