14 papers
Evidence-RL: Towards Evidence-intensive Visual Reasoning
Haojie Huang, Xinlei Yu, Chengming Xu +6
Vision-Language Models (VLMs) should answer from concrete image evidence rather than language priors, dataset shortcuts, or irrelevant visual context. Existing perception-aware pos…
ToolArtist: Tool-Using Unified Multimodal Models for Agentic Image Generation
Jiahao Zhao, Xiaomin Yu, Zhongxiang Sun +5
Text-to-image (T2I) models can produce visually compelling images, yet they remain limited on open-world tasks that require complex semantic understanding, multi-step reasoning, an…
SPEAR: Selection-aware Personalized End-to-end Adaptive Rewriting and Retrieval for Community Search
Wenbin Wu, Yuzhong Wu, Yufan Xu +4
Query reformulation bridges user intent and retrieval in e-commerce search, yet production systems optimize rewrite quality and retrieval effectiveness separately, leaving the two…
TouchThinker: Scaling Tactile Commonsense Reasoning to the Open World with Large-scale Data and Action-aware Representation
Kailin Lyu, Di Wu, Pengwei Zhang +12
Touch is a key modality for embodied agents to understand the physical world. Although recent work has incorporated tactile signals into language systems for tactile commonsense re…
Dual Latent Memory in Vision-Language-Action Models for Robotic Manipulation
Hongyu Qu, Jianzhe Gao, Xiaobin Hu +6
Mainstream Vision-Language-Action (VLA) models predict actions primarily from the current observation under a Markovian assumption, thus struggling with long-horizon, temporally de…
SPOT-E: Test-Time Entropy Shaping with Visual Spotlights for Frozen VLMs
Bo Yin, Xiaobin Hu, Chengming Xu +6
Vision-language models (VLMs) often underperform on evidence intensive tasks because decisive visual evidence are small, localized, and easy to overlook, leading to failures in evi…