All Evals Listings
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Internal link to /explore/lm-evaluation-harness
lm-evaluation-harness
A framework for few-shot evaluation of language models.
Internal link to /explore/hallucination-leaderboard
hallucination-leaderboard
Leaderboard Comparing LLM Performance at Producing Hallucinations when Summarizing Short Documents
Internal link to /explore/adversarial-robustness-toolbox
adversarial-robustness-toolbox
Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams
Internal link to /explore/swe-bench
SWE-bench
[ICLR 2024] SWE-bench: Can Language Models Resolve Real-world Github Issues?
Internal link to /explore/human-eval
human-eval
Code for the paper "Evaluating Large Language Models Trained on Code"
Internal link to /explore/evals
evals
Evals is a framework for evaluating LLMs and LLM systems, and an open-source registry of benchmarks.
Internal link to /explore/evalplus
evalplus
Rigourous evaluation of LLM-synthesized code - NeurIPS 2023 & COLM 2024
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