8 papers
Argus: Evidence Assembly for Scalable Deep Research Agents
Zhen Zhang, Liangcai Su, Zhuo Chen +7
Deep research agents have achieved remarkable progress on complex information seeking tasks. Even long ReAct style rollouts explore only a single trajectory, while recent state of…
From Table to Cell: Attention for Better Reasoning with TABALIGN
Tung Sum Thomas Kwok, Zeyong Zhang, Xinyu Wang +6
Multi-step LLM reasoning over structured tables fails because planning and execution share no explicit cell-grounding contract. Existing methods constrain the planner to a left-to-…
R^2-Mem: Reflective Experience for Memory Search
Xinyuan Wang, Wenyu Mao, Junkang Wu +2
Deep search has recently emerged as a promising paradigm for enabling agents to retrieve fine-grained historical information without heavy memory pre-managed. However, existing dee…
LearnMate^2: Design and Evaluation of an LLM-powered Personalized and Adaptive Support System for Online Learning
Xinyu Jessica Wang, Christine P. Lee, Bilge Mutlu
Personalization is crucial for effective learning, yet online learning, designed for widespread availability and open access, lacks personalized guidance. Recent advancements in la…
From History to State: Constant-Context Skill Learning for LLM Agents
Haoyang Xie, Xinyuan Wang, Yancheng Wang +2
Large language model (LLM) agents are increasingly used to operate browsers, files, code and tools, making personal assistants a natural deployment target. Yet personal agents face…
U-Define: Designing User Workflows for Hard and Soft Constraints in LLM-Based Planning
Christine P Lee, Xinyu Jessica Wang, Aws Albarghouthi +2
LLMs are increasingly used for end-user task planning, yet their black-box nature limits users' ability to ensure reliability and control. While recent systems incorporate verifica…