2 citations · 2 across the 10 of their papers we have counts for
10 papers
Robo-Blocks: Generative Scaffolding in End-User Design and Programming of Social Robots
Arissa J. Sato, Callie Y. Kim, Nathan Thomas White +4
Programming social robots is challenging for novice robot programmers due to required expertise in planning, interaction design, and programming. While large language models (LLMs)…
MedGuideX: Internalizing Decision Logic from Executable Guidelines into Large Language Models for Clinical Reasoning
Yuhao Shen, Lang Cao, Simo Du +4
Clinical practice guidelines (CPGs) encode evidence-based decision logic that clinicians apply by evaluating patient variables, conditional criteria, and recommendation rules. Howe…
Search More, Think Less: Rethinking Long-Horizon Agentic Search for Efficiency and Generalization
Qianben Chen, Tianrui Qin, King Zhu +21
Recent deep research agents primarily improve performance by scaling reasoning depth, but this leads to high inference cost and latency in search-intensive scenarios. Moreover, gen…
PersonaDual: Balancing Personalization and Objectivity via Adaptive Reasoning
Xiaoyou Liu, Xinyi Mou, Shengbin Yue +5
As users increasingly expect LLMs to align with their preferences, personalized information becomes valuable. However, personalized information can be a double-edged sword: it can…
How Far Are We from Genuinely Useful Deep Research Agents?
Dingling Zhang, He Zhu, Jincheng Ren +15
Deep Research Agents (DRAs) aim to automatically produce analyst-level reports through iterative information retrieval and synthesis. However, most existing DRAs were validated on…
O-Mem: Omni Memory System for Personalized, Long Horizon, Self-Evolving Agents
Piaohong Wang, Motong Tian, Jiaxian Li +8
Recent advancements in LLM-powered agents have demonstrated significant potential in generating human-like responses; however, they continue to face challenges in maintaining long-…
Towards Personalized Deep Research: Benchmarks and Evaluations
Yuan Liang, Jiaxian Li, Yuqing Wang +11
Deep Research Agents (DRAs) can autonomously conduct complex investigations and generate comprehensive reports, demonstrating strong real-world potential. However, existing evaluat…
Data Uniformity Improves Training Efficiency and More, with a Convergence Framework Beyond the NTK Regime
Yuqing Wang, Shangding Gu
Data selection plays a crucial role in data-driven decision-making, including in large language models (LLMs), and is typically task-dependent. Properties such as data quality and…
SPORTU: A Comprehensive Sports Understanding Benchmark for Multimodal Large Language Models
Haotian Xia, Zhengbang Yang, Junbo Zou +10
Multimodal Large Language Models (MLLMs) are advancing the ability to reason about complex sports scenarios by integrating textual and visual information. To comprehensively evalua…
Development of Data Evaluation Benchmark for Data Wrangling Recommendation System
Yuqing Wang, Anna Fariha
CoWrangler is a data-wrangling recommender system designed to streamline data processing tasks. Recognizing that data processing is often time-consuming and complex for novice user…