4 citations · 9 across the 19 of their papers we have counts for
9 papers · 1 filter
ReTAC: Residual Test-Time Agentic Computation for Video Spatial Reasoning
Yike Wu, Keyan Chen, Qixiong Wang +6
Test-time agentic computation can improve multimodal large language models (MLLMs) through planning, tool use, iterative perception, and reflection, but indiscriminate computation…
Rubric-Aware On-Policy Self-Distillation for LLM Personalization
Yilun Qiu, Xiaoyan Zhao, Chengbing Wang +6
LLM personalization aims to generate responses aligned with individual users' preferences and needs. User-specific rubrics make these expectations explicit, providing direct superv…
Revisit to Segment: Working Memory Distillation for Reasoning Segmentation
Cilin Yan, Yilun Qiu, Wanyang Zhang +4
Multimodal large language models (MLLMs) have approached image segmentation by reasoning about visual content and predicting target locations. Their generated responses contain rea…
SPAR: Semantic-Pixel Self-Alignment and Adaptive Routing for Unified Multimodal Models
Hongxiang Li, Hongxu Chen, Chenyang Zhu +5
Multimodal Large Language Models (MLLMs) have achieved remarkable success in visual understanding but remain constrained in visual generation due to the fundamental feature discrep…
Impostor: An Agent-Curated Benchmark for Realistic AIGC Manipulation Localization
Zhenliang Li, Yutao Hu, Qixiong Wang +5
Recent advances in generative image editing have improved the realism and controllability of localized image manipulation, raising new challenges for image manipulation detection a…
Preference-Aware Rubric Learning for Personalized Evaluation
Yilun Qiu, Xiaoyan Zhao, Yang Zhang +7
As Large Language Models (LLMs) evolve from general-purpose assistants to user-centric agents, personalization has become central to aligning model behavior with individual prefere…
AgentCVR: Active Multi-Agent Cross-Video Reasoning via Script-Simulated Reinforcement Learning
Yilun Qiu, Jiahe Wang, Cilin Yan +4
Cross-Video Reasoning (CVR) has emerged as a critical frontier in multimodal intelligence, requiring models to retrieve, align, and aggregate evidence distributed across multiple v…
VideoSeeker: Incentivizing Instance-level Video Understanding via Native Agentic Tool Invocation
Yiming Zhao, Yu Zeng, Wenxuan Huang +11
Large Vision-Language Models (LVLMs) have shown significant progress in video understanding, yet they face substantial challenges in tasks requiring precise spatiotemporal localiza…
Weaver: End-to-End Agentic System Training for Video Interleaved Reasoning
Yudi Shi, Shangzhe Di, Qirui Chen +5
Video reasoning constitutes a comprehensive assessment of a model's capabilities, as it demands robust perceptual and interpretive skills, thereby serving as a means to explore the…