1 citations · 1 across the 7 of their papers we have counts for
7 papers
Single-Agent Scaling Fails Multi-Agent Intelligence: Towards Foundation Models with Native Multi-Agent Intelligence
Shuyue Hu, Haoyang Yan, Yiqun Zhang +3
Foundation models (FMs) are increasingly assuming the role of the ''brain'' of AI agents. While recent efforts have begun to equip FMs with native single-agent abilities -- such as…
Learning-Based Automated Adversarial Red-Teaming for Robustness Evaluation of Large Language Models
Zhang Wei, Hanxuan Chen, Peilu Hu +19
Red-teaming is becoming a central part of large language model (LLM) safety evaluation, yet current practice still relies heavily on expert-written prompts or fixed benchmark suite…
Batch Prompting Suppresses Overthinking Reasoning Under Constraint: How Batch Prompting Suppresses Overthinking in Reasoning Models
Saurabh Srivastava, Janit Bidhan, Hao Yan +7
Large Reasoning Models (LRMs) achieve strong performance through explicit chain-of-thought reasoning but suffer from \textit{overthinking}: generating excessive reasoning tokens ev…
Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation
Hao Yan, Swapneel Suhas Vaidya, Xiaokuan Zhang +1
Large Language Models have become powerful tools for programming. However, they often overlook essential security practices, producing insecure code with vulnerabilities. Despite t…
Can LLMs Simulate Personas with Reversed Performance? A Systematic Investigation for Counterfactual Instruction Following in Math Reasoning Context
Sai Adith Senthil Kumar, Hao Yan, Saipavan Perepa +2
Large Language Models (LLMs) are now increasingly widely used to simulate personas in virtual environments, leveraging their instruction-following capability. However, we discovere…
Distilling Desired Comments for Enhanced Code Review with Large Language Models
Yongda Yu, Lei Zhang, Guoping Rong +9
There has been a growing interest in using Large Language Models (LLMs) for code review thanks to their proven proficiency in code comprehension. The primary objective of most revi…
Advancing Prompt Recovery in NLP: A Deep Dive into the Integration of Gemma-2b-it and Phi2 Models
Jianlong Chen, Wei Xu, Zhicheng Ding +3
Prompt recovery, a crucial task in natural language processing, entails the reconstruction of prompts or instructions that language models use to convert input text into a specific…