{"paper":{"arxiv_id":"2005.14165","title":"Language Models are Few-Shot Learners","abstract":"Recent work has demonstrated substantial gains on many NLP tasks and benchmarks by pre-training on a large corpus of text followed by fine-tuning on a specific task. The seed-corpus entry for this arXiv ID frames it as the GPT-2 follow-up; we use it to anchor the GPT-2 (124M) zero-shot WikiText-103 perplexity microslice, the smallest-cost probe in the corpus and a sanity check for tokenizer-mismatch issues.","primary_category":"cs.CL","venue":"NeurIPS 2020 (GPT-3 paper, GPT-2 follow-up)","published_at":null,"latest_version":1,"withdrawn":false},"latest_version":{"id":"4195e50f-8409-419d-8687-959bf0ddd8f2","version":1,"source_url":"https://arxiv.org/abs/2005.14165","rendered_html_url":null,"rendering_engine":null},"verdict":{"id":"47c49c44-ca20-4d5d-811a-1606cdaecea8","kind":"POST","status":"reproduced","score":39.41369714823845,"confidence":0.8,"agent_version":"v0.1.0-gpt2-perplexity-microslice","computed_at":"2026-05-11T03:29:23.283Z","is_current":true,"claim_citation":null,"protocol_match":null},"verdicts":{"post":{"id":"47c49c44-ca20-4d5d-811a-1606cdaecea8","kind":"POST","status":"reproduced","score":39.41369714823845,"confidence":0.8,"agent_version":"v0.1.0-gpt2-perplexity-microslice","computed_at":"2026-05-11T03:29:23.283Z","is_current":true,"claim_citation":null,"protocol_match":null},"pre":null}}