7 citations · 16 across the 9 of their papers we have counts for
8 papers · 1 filter
MultiAgent Collaboration Attack: Investigating Adversarial Attacks in Large Language Model Collaborations via Debate
Alfonso Amayuelas, Xianjun Yang, Antonis Antoniades +3
Large Language Models (LLMs) have shown exceptional results on current benchmarks when working individually. The advancement in their capabilities, along with a reduction in parame…
Faithful Logical Reasoning via Symbolic Chain-of-Thought
Jundong Xu, Hao Fei, Liangming Pan +3
While the recent Chain-of-Thought (CoT) technique enhances the reasoning ability of large language models (LLMs) with the theory of mind, it might still struggle in handling logica…
SciAgent: Tool-augmented Language Models for Scientific Reasoning
Yubo Ma, Zhibin Gou, Junheng Hao +8
Scientific reasoning poses an excessive challenge for even the most advanced Large Language Models (LLMs). To make this task more practical and solvable for LLMs, we introduce a ne…
A Survey on Detection of LLMs-Generated Content
Xianjun Yang, Liangming Pan, Xuandong Zhao +4
The burgeoning capabilities of advanced large language models (LLMs) such as ChatGPT have led to an increase in synthetic content generation with implications across a variety of s…
QACHECK: A Demonstration System for Question-Guided Multi-Hop Fact-Checking
Liangming Pan, Xinyuan Lu, Min-Yen Kan +1
Fact-checking real-world claims often requires complex, multi-step reasoning due to the absence of direct evidence to support or refute them. However, existing fact-checking system…
Investigating Zero- and Few-shot Generalization in Fact Verification
Liangming Pan, Yunxiang Zhang, Min-Yen Kan
In this paper, we explore zero- and few-shot generalization for fact verification (FV), which aims to generalize the FV model trained on well-resourced domains (e.g., Wikipedia) to…