4 papers
Weights to Code: Extracting Interpretable Algorithms from the Discrete Transformer
Yifan Zhang, Wei Bi, Kechi Zhang +3
Algorithm extraction aims to synthesize executable programs directly from models trained on algorithmic tasks, enabling de novo recovery of executable mechanisms from weights witho…
Finite State Automata Inside Transformers with Chain-of-Thought: A Mechanistic Study on State Tracking
Yifan Zhang, Wenyu Du, Dongming Jin +2
Chain-of-thought (CoT) significantly enhances the performance of large language models (LLMs) across a wide range of tasks, and prior research shows that CoT can theoretically incr…
MEEL: Multi-Modal Event Evolution Learning
Zhengwei Tao, Zhi Jin, Junqiang Huang +5
Multi-modal Event Reasoning (MMER) endeavors to endow machines with the ability to comprehend intricate event relations across diverse data modalities. MMER is fundamental and unde…
A Comprehensive Evaluation on Event Reasoning of Large Language Models
Zhengwei Tao, Zhi Jin, Yifan Zhang +7
Event reasoning is a fundamental ability that underlies many applications. It requires event schema knowledge to perform global reasoning and needs to deal with the diversity of th…