1 citations · 2 across the 6 of their papers we have counts for
7 papers
When Clipping Reverses Correction: Failure Dynamics of Pointwise Forward-KL On-Policy Self-Distillation
Di Huang, Hao Li, Yixin Chen +1
On-policy self-distillation (OPSD) trains a student on its own generated responses using feedback from the same model conditioned on privileged information. On mathematical reasoni…
Context-Aware Classification and Grading of Sensitive Information in Online Conversational Health Data
Yiwei Yan, Hao Li, Hua He +3
Online medical consultations contain sensitive health information whose privacy implications depend not only on the entities mentioned but also on how those entities are described…
Unveiling and Causalizing CoT: A Causal Pespective
Jiarun Fu, Lizhong Ding, Hao Li +3
Although Chain-of-Thought (CoT) has achieved remarkable success in enhancing the reasoning ability of large language models (LLMs), the mechanism of CoT remains a ``black box''. Ev…
RuozhiBench: Evaluating LLMs with Logical Fallacies and Misleading Premises
Zenan Zhai, Hao Li, Xudong Han +4
Recent advances in large language models (LLMs) have shown that they can answer questions requiring complex reasoning. However, their ability to identify and respond to text contai…
Skewed Memorization in Large Language Models: Quantification and Decomposition
Hao Li, Di Huang, Ziyu Wang +1
Memorization in Large Language Models (LLMs) poses privacy and security risks, as models may unintentionally reproduce sensitive or copyrighted data. Existing analyses focus on ave…
NYK-MS: A Well-annotated Multi-modal Metaphor and Sarcasm Understanding Benchmark on Cartoon-Caption Dataset
Ke Chang, Hao Li, Junzhao Zhang +1
Metaphor and sarcasm are common figurative expressions in people's communication, especially on the Internet or the memes popular among teenagers. We create a new benchmark named N…
HealthQ: Unveiling Questioning Capabilities of LLM Chains in Healthcare Conversations
Ziyu Wang, Hao Li, Di Huang +3
Effective patient care in digital healthcare requires large language models (LLMs) that not only answer questions but also actively gather critical information through well-crafted…