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cs.CL2024★ 15 cited
LLM Evaluators Recognize and Favor Their Own Generations
Arjun Panickssery, Samuel R. Bowman, Shi Feng
Self-evaluation using large language models (LLMs) has proven valuable not only in benchmarking but also methods like reward modeling, constitutional AI, and self-refinement. But n…
cs.CL2024
REBUS: A Robust Evaluation Benchmark of Understanding Symbols
Andrew Gritsevskiy, Arjun Panickssery, Aaron Kirtland +7
We propose a new benchmark evaluating the performance of multimodal large language models on rebus puzzles. The dataset covers 333 original examples of image-based wordplay, cluing…