2 citations · 5 across the 10 of their papers we have counts for
4 papers · 1 filter
Learning Personalized Agents from Human Feedback
Kaiqu Liang, Julia Kruk, Shengyi Qian +9
Modern AI agents are powerful but often fail to align with the idiosyncratic, evolving preferences of individual users. Prior approaches typically rely on static datasets, either t…
The Geometry of Reasoning: Flowing Logics in Representation Space
Yufa Zhou, Yixiao Wang, Xunjian Yin +2
We study how large language models (LLMs) ``think'' through their representation space. We propose a novel geometric framework that models an LLM's reasoning as flows -- embedding…
Generalizability of Large Language Model-Based Agents: A Comprehensive Survey
Minxing Zhang, Yi Yang, Roy Xie +3
Large Language Model (LLM)-based agents have emerged as a new paradigm that extends LLMs' capabilities beyond text generation to dynamic interaction with external environments. By…
Synatra: Turning Indirect Knowledge into Direct Demonstrations for Digital Agents at Scale
Tianyue Ou, Frank F. Xu, Aman Madaan +7
LLMs can now act as autonomous agents that interact with digital environments and complete specific objectives (e.g., arranging an online meeting). However, accuracy is still far f…