258 citations · 353 across the 46 of their papers we have counts for
13 papers · 1 filter
BasketEvent: Understanding Who Did What and When in Basketball Videos
Yu Zhang, Jiayuan Rao, Haoning Wu +1
Comprehensive basketball video understanding requires resolving not only what event occurs, but also who is responsible and when the key evidence appears. However, exist- ing metho…
A Vision-language Framework for Comparative Reasoning in Radiology
Tengfei Zhang, Ziheng Zhao, Xiaoman Zhang +5
Medical imaging artificial intelligence has achieved strong performance in isolated image interpretation, but remains poorly aligned with radiological practice, where diagnosis and…
Evaluating Large Language Models in Dynamic Clinical Decision-Making with Standardized Patient Cases
Cheng Liang, Pengcheng Qiu, Ya Zhang +3
Large language models (LLMs) are increasingly proposed as clinical agents, yet static, single-turn benchmarks cannot capture how a model dynamically delivers care across an encount…
A Sanity Check on Composed Image Retrieval
Yikun Liu, Jiangchao Yao, Weidi Xie +1
Composed Image Retrieval (CIR) aims to retrieve a target image based on a query composed of a reference image, and a relative caption that specifies the desired modification. Despi…
GenTac: Generative Modeling and Forecasting of Soccer Tactics
Jiayuan Rao, Tianlin Gui, Haoning Wu +2
Modeling open-play soccer tactics is a formidable challenge due to the stochastic, multi-agent nature of the game. Existing computational approaches typically produce single, deter…
POINTS-Long: Adaptive Dual-Mode Visual Reasoning in MLLMs
Haicheng Wang, Yuan Liu, Yikun Liu +9
Multimodal Large Language Models (MLLMs) have recently demonstrated remarkable capabilities in cross-modal understanding and generation. However, the rapid growth of visual token s…
POINTS-Seeker: An Open Recipe for Multimodal Search Agents with Visual Memory Management
Yikun Liu, Yuan Liu, Haicheng Wang +6
Large Multimodal Models (LMMs) excel at visual perception but struggle with real-time, knowledge-intensive queries due to their reliance on static parametric knowledge. While multi…
SpotSound: Enhancing Large Audio-Language Models with Fine-Grained Temporal Grounding
Luoyi Sun, Xiao Zhou, Zeqian Li +3
Large Audio-Language Models (ALMs) have recently demonstrated remarkable capabilities in holistic audio understanding, yet they remain unreliable for temporal grounding, i.e., the…
Predicting Neuromodulation Outcome for Parkinson's Disease with Generative Virtual Brain Model
Siyuan Du, Siyi Li, Shuwei Bai +10
Parkinson's disease (PD) affects over ten million people worldwide. Although temporal interference (TI) and deep brain stimulation (DBS) are promising therapies, inter-individual v…
Re-purposing Multimodal Large Language Models for Audio-Text Retrieval
Jilan Xu, Carl Thomé, Danijela Horak +2
Audio-text retrieval is crucial for bridging acoustic signals and natural language. While contrastive dual-encoder architectures like CLAP have shown promise, they are fundamentall…
VersaViT: Enhancing MLLM Vision Backbones via Task-Guided Optimization
Yikun Liu, Yuan Liu, Shangzhe Di +8
Multimodal Large Language Models (MLLMs) have recently achieved remarkable success in visual-language understanding, demonstrating superior high-level semantic alignment within the…
PhenoLIP: Integrating Phenotype Ontology Knowledge into Medical Vision-Language Pretraining
Cheng Liang, Chaoyi Wu, Weike Zhao +3
Recent progress in large-scale CLIP-like vision-language models(VLMs) has greatly advanced medical image analysis. However, most existing medical VLMs still rely on coarse image-te…
FAIL: Flow Matching Adversarial Imitation Learning for Image Generation
Yeyao Ma, Chen Li, Xiaosong Zhang +2
Post-training of flow matching models-aligning the output distribution with a high-quality target-is mathematically equivalent to imitation learning. While Supervised Fine-Tuning m…