4 citations · 5 across the 4 of their papers we have counts for
4 papers
Position: Explainability Research Must Prioritize Foundations over Ad-hoc Methods
Michal Moshkovitz, Suraj Srinivas, Lesia Semenova +7
Despite the proliferation of Explainable AI (XAI) techniques -- from feature attributions to sparse autoencoders -- explanations rarely influence real-world workflows. In practice,…
Large Language Model Agent: A Survey on Methodology, Applications and Challenges
Junyu Luo, Weizhi Zhang, Ye Yuan +23
The era of intelligent agents is upon us, driven by revolutionary advancements in large language models. Large Language Model (LLM) agents, with goal-driven behaviors and dynamic a…
Towards Unified Attribution in Explainable AI, Data-Centric AI, and Mechanistic Interpretability
Shichang Zhang, Tessa Han, Usha Bhalla +1
The increasing complexity of AI systems has made understanding their behavior critical. Numerous interpretability methods have been developed to attribute model behavior to three k…
Self-Control of LLM Behaviors by Compressing Suffix Gradient into Prefix Controller
Min Cai, Yuchen Zhang, Shichang Zhang +5
We propose SelfControl, an inference-time model control method utilizing gradients to control the behavior of large language models (LLMs) without explicit human annotations. Given…