3 citations · 6 across the 16 of their papers we have counts for
8 papers · 1 filter
TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots
Tianyu Liu, Weihao Xuan, Hao Wu +15
Advances in AI have introduced several strong models in computational pathology to usher it into the era of multi-modal diagnosis, analysis, and interpretation. However, the curren…
DeepSearch: Overcome the Bottleneck of Reinforcement Learning with Verifiable Rewards via Monte Carlo Tree Search
Fang Wu, Weihao Xuan, Heli Qi +4
Although RLVR has become an essential component for developing advanced reasoning skills in language models, contemporary studies have documented training plateaus after thousands…
Position: The Hidden Costs and Measurement Gaps of Reinforcement Learning with Verifiable Rewards
Fang Wu, Aaron Tu, Weihao Xuan +21
Reinforcement learning with verifiable rewards (RLVR) is a practical, scalable way to improve large language models on math, code, and other structured tasks. However, we argue tha…
VeriWeb: Verifiable Long-Chain Web Benchmark for Agentic Information-Seeking
Shunyu Liu, Minghao Liu, Huichi Zhou +31
Recent advances have showcased the extraordinary capabilities of Large Language Model (LLM) agents in tackling web-based information-seeking tasks. However, existing efforts mainly…
Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models
Weihao Xuan, Qingcheng Zeng, Heli Qi +2
Uncertainty quantification is essential for assessing the reliability and trustworthiness of modern AI systems. Among existing approaches, verbalized uncertainty, where models expr…
DisasterM3: A Remote Sensing Vision-Language Dataset for Disaster Damage Assessment and Response
Junjue Wang, Weihao Xuan, Heli Qi +8
Large vision-language models (VLMs) have made great achievements in Earth vision. However, complex disaster scenes with diverse disaster types, geographic regions, and satellite se…
DynamicVL: Benchmarking Multimodal Large Language Models for Dynamic City Understanding
Weihao Xuan, Junjue Wang, Heli Qi +5
Multimodal large language models (MLLMs) have demonstrated remarkable capabilities in visual understanding, but their application to long-term Earth observation analysis remains li…
MMLU-ProX: A Multilingual Benchmark for Advanced Large Language Model Evaluation
Weihao Xuan, Rui Yang, Heli Qi +29
Existing large language model (LLM) evaluation benchmarks primarily focus on English, while current multilingual tasks lack parallel questions that specifically assess cross-lingui…