1 citations · 4 across the 47 of their papers we have counts for
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VistaHop: Benchmarking Long-Horizon Visual DeepSearch
Hang He, Chuhuai Yue, Chengqi Dong +6
Visual DeepSearch tasks require multimodal large language models (MLLMs) to resolve complex visual queries by repeatedly inspecting image regions, grounding reasoning in visual evi…
DiningBench: A Hierarchical Multi-view Benchmark for Perception and Reasoning in the Dietary Domain
Song Jin, Juntian Zhang, Xun Zhang +6
Recent advancements in Vision-Language Models (VLMs) have revolutionized general visual understanding. However, their application in the food domain remains constrained by benchmar…
Training Multi-Image Vision Agents via End2End Reinforcement Learning
Chengqi Dong, Chuhuai Yue, Hang He +7
Recent VLM-based agents aim to replicate OpenAI O3's "thinking with images" via tool use, yet most open-source methods restrict inputs to a single image, limiting their applicabili…
ViPER: Empowering the Self-Evolution of Visual Perception Abilities in Vision-Language Model
Juntian Zhang, Song Jin, Chuanqi Cheng +8
The limited capacity for fine-grained visual perception presents a critical bottleneck for Vision-Language Models (VLMs) in real-world applications. Addressing this is challenging…
SSL4RL: Revisiting Self-supervised Learning as Intrinsic Reward for Visual-Language Reasoning
Xiaojun Guo, Runyu Zhou, Yifei Wang +8
Vision-language models (VLMs) have shown remarkable abilities by integrating large language models with visual inputs. However, they often fail to utilize visual evidence adequatel…