most citedCounterBench: Evaluating and Improving Counterfactual Reasoning in Large Language Models

1 citations · 2 across the 6 of their papers we have counts for

collaborators
Showing cs.CLShow all

5 papers · 1 filter

cs.CL2026

REFLEX: Self-Refining Explainable Fact-Checking via Verdict-Anchored Style Control

Chuyi Kong, Wei Gao, Jing Ma +2

The prevalence of fake news on social media demands automated fact-checking systems to provide accurate verdicts with faithful explanations. However, existing large language model…

cs.CL2026

MemRouter: Memory-as-Embedding Routing for Long-Term Conversational Agents

Tianyu Hu, Weikai Lin, Weizhi Zhang +2

Long-term conversational agents must decide which turns to store in external memory, yet recent systems rely on autoregressive LLM generation at every turn to make that decision. W…

cs.CL20261 cited

CounterBench: Evaluating and Improving Counterfactual Reasoning in Large Language Models

Yuefei Chen, Vivek K. Singh, Jing Ma +1

Counterfactual reasoning is widely recognized as one of the most challenging and intricate aspects of causality in artificial intelligence. In this paper, we evaluate the performan…

cs.CL20261 cited

LLM-based Few-Shot Early Rumor Detection with Imitation Agent

Fengzhu Zeng, Qian Shao, Ling Cheng +4

Early Rumor Detection (EARD) aims to identify the earliest point at which a claim can be accurately classified based on a sequence of social media posts. This is especially challen…

cs.CL2025

CausalAbstain: Enhancing Multilingual LLMs with Causal Reasoning for Trustworthy Abstention

Yuxi Sun, Aoqi Zuo, Wei Gao +1

Large Language Models (LLMs) often exhibit knowledge disparities across languages. Encouraging LLMs to \textit{abstain} when faced with knowledge gaps is a promising strategy to re…