1 citations · 2 across the 6 of their papers we have counts for
6 papers
All That Glisters Is Not Gold: A Benchmark for Reference-Free Counterfactual Financial Misinformation Detection
Yuechen Jiang, Zhiwei Liu, Yupeng Cao +10
We introduce RFC Bench, a benchmark for evaluating large language models on financial misinformation under realistic news. RFC Bench operates at the paragraph level and captures th…
On the Limitations of Rank-One Model Editing in Answering Multi-hop Questions
Zhiyuan He, Binghan Chen, Tianxiang Xiong +3
Recent advances in Knowledge Editing (KE), particularly Rank-One Model Editing (ROME), show superior efficiency over fine-tuning and in-context learning for updating single-hop fac…
How does Chain of Thought Think? Mechanistic Interpretability of Chain-of-Thought Reasoning with Sparse Autoencoding
Xi Chen, Aske Plaat, Niki van Stein
Chain-of-thought (CoT) prompting boosts Large Language Models accuracy on multi-step tasks, yet whether the generated "thoughts" reflect the true internal reasoning process is unre…
Debate-Feedback: A Multi-Agent Framework for Efficient Legal Judgment Prediction
Xi Chen, Mao Mao, Shuo Li +1
The use of AI in legal analysis and prediction (LegalAI) has gained widespread attention, with past research focusing on retrieval-based methods and fine-tuning large models. Howev…
MindStar: Enhancing Math Reasoning in Pre-trained LLMs at Inference Time
Jikun Kang, Xin Zhe Li, Xi Chen +9
Although Large Language Models (LLMs) achieve remarkable performance across various tasks, they often struggle with complex reasoning tasks, such as answering mathematical question…
LaFFi: Leveraging Hybrid Natural Language Feedback for Fine-tuning Language Models
Qianxi Li, Yingyue Cao, Jikun Kang +4
Fine-tuning Large Language Models (LLMs) adapts a trained model to specific downstream tasks, significantly improving task-specific performance. Supervised Fine-Tuning (SFT) is a c…