93 citations · 212 across the 24 of their papers we have counts for
9 papers · 1 filter
Formalize Once, Edit the Rest: Efficient Lean-Based Answer Selection for Math Reasoning
Ji Feng, Zhouxing Shi
With large language models (LLMs) increasingly applied to mathematical reasoning, formal proof assistants such as Lean can be leveraged to verify reasoning outputs with machine-che…
Evaluating the Robustness of Proof Autoformalization in Lean 4
Zhengtao Gui, Sheng Yang, Zhouxing Shi
Proof autoformalization aims to translate a mathematical informal proof in natural language into a formal proof in a formal language such as Lean 4. Existing LLM-based models for p…
PIKA: Expert-Level Synthetic Datasets for Post-Training Alignment from Scratch
Shangjian Yin, Shining Liang, Wenbiao Ding +4
High-quality instruction data is critical for LLM alignment, yet existing open-source datasets often lack efficiency, requiring hundreds of thousands of examples to approach propri…
Defending LLMs against Jailbreaking Attacks via Backtranslation
Yihan Wang, Zhouxing Shi, Andrew Bai +1
Although many large language models (LLMs) have been trained to refuse harmful requests, they are still vulnerable to jailbreaking attacks which rewrite the original prompt to conc…
Improving the Generation Quality of Watermarked Large Language Models via Word Importance Scoring
Yuhang Li, Yihan Wang, Zhouxing Shi +1
The strong general capabilities of Large Language Models (LLMs) bring potential ethical risks if they are unrestrictedly accessible to malicious users. Token-level watermarking ins…
Red Teaming Language Model Detectors with Language Models
Zhouxing Shi, Yihan Wang, Fan Yin +3
The prevalence and strong capability of large language models (LLMs) present significant safety and ethical risks if exploited by malicious users. To prevent the potentially decept…
On the Sensitivity and Stability of Model Interpretations in NLP
Fan Yin, Zhouxing Shi, Cho-Jui Hsieh +1
Recent years have witnessed the emergence of a variety of post-hoc interpretations that aim to uncover how natural language processing (NLP) models make predictions. Despite the su…
Knowledge-Aided Open-Domain Question Answering
Mantong Zhou, Zhouxing Shi, Minlie Huang +1
Open-domain question answering (QA) aims to find the answer to a question from a large collection of documents.Though many models for single-document machine comprehension have ach…
A Deep Sequential Model for Discourse Parsing on Multi-Party Dialogues
Zhouxing Shi, Minlie Huang
Discourse structures are beneficial for various NLP tasks such as dialogue understanding, question answering, sentiment analysis, and so on. This paper presents a deep sequential m…