4 citations · 8 across the 12 of their papers we have counts for
13 papers
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…
SCIR: A Self-Correcting Iterative Refinement Framework for Enhanced Information Extraction Based on Schema
Yushen Fang, Jianjun Li, Mingqian Ding +3
Although Large language Model (LLM)-powered information extraction (IE) systems have shown impressive capabilities, current fine-tuning paradigms face two major limitations: high t…
POLIS-Bench: Towards Multi-Dimensional Evaluation of LLMs for Bilingual Policy Tasks in Governmental Scenarios
Tingyue Yang, Junchi Yao, Yuhui Guo +1
We introduce POLIS-Bench, the first rigorous, systematic evaluation suite designed for LLMs operating in governmental bilingual policy scenarios. Compared to existing benchmarks, P…
Reflections from Research Roundtables at the Conference on Health, Inference, and Learning (CHIL) 2025
Emily Alsentzer, Marie-Laure Charpignon, Bill Chen +90
The 6th Annual Conference on Health, Inference, and Learning (CHIL 2025), hosted by the Association for Health Learning and Inference (AHLI), was held in person on June 25-27, 2025…
TARS: MinMax Token-Adaptive Preference Strategy for Hallucination Reduction in MLLMs
Kejia Zhang, Keda Tao, Zhiming Luo +3
Multimodal large language models (MLLMs) are prone to hallucinations, generating plausible but visually ungrounded outputs, partly because direct preference optimization (DPO) over…
AutoGEEval++: A Multi-Level and Multi-Geospatial-Modality Automated Evaluation Framework for Large Language Models in Geospatial Code Generation on Google Earth Engine
Shuyang Hou, Zhangxiao Shen, Huayi Wu +10
Geospatial code generation is becoming a key frontier in integrating artificial intelligence with geo-scientific analysis, yet standardised automated evaluation tools for this task…
Agent-based Condition Monitoring Assistance with Multimodal Industrial Database Retrieval Augmented Generation
Karl Löwenmark, Daniel Strömbergsson, Chang Liu +2
Condition monitoring (CM) plays a crucial role in ensuring reliability and efficiency in the process industry. Although computerised maintenance systems effectively detect and clas…
Design and evaluation of AI copilots -- case studies of retail copilot templates
Michal Furmakiewicz, Chang Liu, Angus Taylor +1
Building a successful AI copilot requires a systematic approach. This paper is divided into two sections, covering the design and evaluation of a copilot respectively. A case study…
Future-proofing geotechnics workflows: accelerating problem-solving with large language models
Stephen Wu, Yu Otake, Daijiro Mizutani +16
The integration of Large Language Models (LLMs) like ChatGPT into the workflows of geotechnical engineering has a high potential to transform how the discipline approaches problem-…