4 citations · 8 across the 12 of their papers we have counts for
5 papers · 1 filter
Complex Problem Solving in Large Language Models: A Statistical Control Survey and Diagnostic Framework
Jiazhang Cai, Tao Wang, Ruidong Zhang +35
Complex problem solving (CPS) with large language models (LLMs) is often framed as a matter of stronger reasoning or longer generation. Yet early-step error amplification, prompt b…
RoboGene: Diversity-Driven Agentic Task Generation Framework for VLA Pre-training
Yixue Zhang, Kun Wu, Zhi Gao +12
The pursuit of general-purpose robotic manipulation is hindered by the scarcity of diverse, real-world interaction data. Unlike large-scale web vision-language data, robotic data c…
Behavioral Indicators of Overreliance During Interaction with Conversational Language Models
Chang Liu, Qinyi Zhou, Xinjie Shen +3
LLMs are now embedded in a wide range of everyday scenarios. However, their inherent hallucinations risk hiding misinformation in fluent responses, raising concerns about overrelia…
DeepSearchQA: Bridging the Comprehensiveness Gap for Deep Research Agents
Nikita Gupta, Riju Chatterjee, Lukas Haas +9
We introduce DeepSearchQA, a 900-prompt benchmark for evaluating agents on difficult multi-step information-seeking tasks across 17 different fields. Unlike traditional benchmarks…
Me-Agent: A Personalized Mobile Agent with Two-Level User Habit Learning for Enhanced Interaction
Shuoxin Wang, Chang Liu, Gowen Loo +5
Large Language Model (LLM)-based mobile agents have made significant performance advancements. However, these agents often follow explicit user instructions while overlooking perso…