ENTITY
Yegon Kim
Yegon Kim
PulseAugur coverage of Yegon Kim — every cluster mentioning Yegon Kim across labs, papers, and developer communities, ranked by signal.
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Papers · 30d
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RECENT · PAGE 1/1 · 2 TOTAL
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New method decouples LLM correctness from verifiability to combat legibility tax
Researchers have developed a new method to address the "legibility tax" in prover-verifier games used for checking large language model outputs. This tax refers to the accuracy degradation that occurs when models are tr…
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New LLM techniques enhance reasoning via iterative refinement and optimized looping · 5 sources tracked
Researchers have developed new methods to improve the reasoning capabilities of large language models (LLMs) through test-time scaling. The REVES framework uses a two-stage iterative process to augment training data and…