3 papers
cs.AI2026
Bridging the Know-Act Gap via Task-Level Autoregressive Reasoning
Jihyun Janice Ahn, Ryo Kamoi, Berk Atil +34
LLMs often generate seemingly valid answers to flawed or ill-posed inputs. This is not due to missing knowledge: under discriminative prompting, the same models can mostly identify…
cs.CL2025
Prompt-Reverse Inconsistency: LLM Self-Inconsistency Beyond Generative Randomness and Prompt Paraphrasing
Jihyun Janice Ahn, Wenpeng Yin
While the inconsistency of LLMs is not a novel topic, prior research has predominantly addressed two types of generative inconsistencies: i) Randomness Inconsistency: running the s…
cs.CL2024
AAAR-1.0: Assessing AI's Potential to Assist Research
Renze Lou, Hanzi Xu, Sijia Wang +15
Numerous studies have assessed the proficiency of AI systems, particularly large language models (LLMs), in facilitating everyday tasks such as email writing, question answering, a…