6 papers
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…
Are Open-Weight LLMs Ready for Social Media Moderation? A Comparative Study on Bluesky
Hsuan-Yu Chou, Wajiha Naveed, Shuyan Zhou +1
As internet access expands, so does exposure to harmful content, increasing the need for effective moderation. Research has demonstrated that large language models (LLMs) can be ef…
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…
WebInject: Prompt Injection Attack to Web Agents
Xilong Wang, John Bloch, Zedian Shao +3
Multi-modal large language model (MLLM)-based web agents interact with webpage environments by generating actions based on screenshots of the webpages. In this work, we propose Web…
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…