2 citations · 5 across the 20 of their papers we have counts for
6 papers · 1 filter
Building Agent Harnesses for Scientific Curation from Multimodal Sources
Sheng Zhang, Qin Liu, Renqian Luo +9
Scientific discovery workflows often depend on structured curation from the literature. This is difficult for current agents because the key evidence is scattered across long text,…
AsgardBench -- Evaluating Visually Grounded Interactive Planning Under Minimal Feedback
Andrea Tupini, Lars Liden, Reuben Tan +2
With AsgardBench we aim to evaluate visually grounded, high-level action sequence generation and interactive planning, focusing specifically on plan adaptation during execution bas…
Multimodal Reinforcement Learning with Adaptive Verifier for AI Agents
Reuben Tan, Baolin Peng, Zhengyuan Yang +15
Agentic reasoning models trained with multimodal reinforcement learning (MMRL) have become increasingly capable, yet they are almost universally optimized using sparse, outcome-bas…
OctoMed: Data Recipes for State-of-the-Art Multimodal Medical Reasoning
Timothy Ossowski, Sheng Zhang, Qianchu Liu +5
High-quality and carefully curated data is a cornerstone of training medical large language models, as it directly impacts both generalization and robustness to unseen clinical tas…
The Illusion of Readiness in Health AI
Yu Gu, Jingjing Fu, Xiaodong Liu +29
Large language models have demonstrated remarkable performance in a wide range of medical benchmarks. Yet underneath the seemingly promising results lie salient growth areas, espec…
Socratis: Are large multimodal models emotionally aware?
Katherine Deng, Arijit Ray, Reuben Tan +3
Existing emotion prediction benchmarks contain coarse emotion labels which do not consider the diversity of emotions that an image and text can elicit in humans due to various reas…