36 citations · 53 across the 12 of their papers we have counts for
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cs.CL2024
Advancing Large Language Models to Capture Varied Speaking Styles and Respond Properly in Spoken Conversations
Guan-Ting Lin, Cheng-Han Chiang, Hung-yi Lee
In spoken dialogue, even if two current turns are the same sentence, their responses might still differ when they are spoken in different styles. The spoken styles, containing para…
cs.CL2024
Merging Facts, Crafting Fallacies: Evaluating the Contradictory Nature of Aggregated Factual Claims in Long-Form Generations
Cheng-Han Chiang, Hung-yi Lee
Long-form generations from large language models (LLMs) contain a mix of factual and non-factual claims, making evaluating factuality difficult. Prior works evaluate the factuality…
cs.CL2024★ 1 cited
Over-Reasoning and Redundant Calculation of Large Language Models
Cheng-Han Chiang, Hung-yi Lee
Large language models (LLMs) can solve problems step-by-step. While this chain-of-thought (CoT) reasoning boosts LLMs' performance, it is unclear if LLMs \textit{know} when to use…