2 citations · 5 across the 17 of their papers we have counts for
20 papers
MRC-MMAgent: Reinforcement Learning for Multi-Role Collaboration in Multimodal Tool-Using Agents
Shengqin Wang, Jie Jin, Xiaofan Li +8
Multimodal tool-using agents augment vision-language models with access to external information and capabilities, enabling them to solve knowledge-intensive and visually complex ta…
VideoSearcher: Empowering Video Deep Research with Multi-Tool Agentic Reasoning via Reinforcement Learning
Zhenkun Gao, Yicheng Bao, Jinlong Peng +13
Video understanding is moving beyond closed-context perception toward open-world evidence exploration, a paradigm formalized as Video Deep Research (VDR). However, existing multimo…
DR-MMSearchAgent: Deepening Reasoning in Multimodal Search Agents
Shengqin Wang, Wentao Yan, Huichi Zhou +4
Agentic multimodal models have garnered significant attention for their ability to leverage external tools to tackle complex tasks. However, it is observed that such agents often m…
Memory Intelligence Agent
Jingyang Qiao, Weicheng Meng, Yu Cheng +6
Deep research agents (DRAs) integrate LLM reasoning with external tools. Memory systems enable DRAs to leverage historical experiences, which are essential for efficient reasoning…
DiPO: Disentangled Perplexity Policy Optimization for Fine-grained Exploration-Exploitation Trade-Off
Xiaofan Li, Ming Yang, Zhiyuan Ma +9
Reinforcement Learning with Verifiable Rewards (RLVR) has catalyzed significant advances in the reasoning capabilities of Large Language Models (LLMs). However, effectively managin…
Continual-NExT: A Unified Comprehension And Generation Continual Learning Framework
Jingyang Qiao, Zhizhong Zhang, Xin Tan +3
Dual-to-Dual MLLMs refer to Multimodal Large Language Models, which can enable unified multimodal comprehension and generation through text and image modalities. Although exhibitin…
Vision-language models lag human performance on physical dynamics and intent reasoning
Tianjun Gu, Jingyu Gong, Zhizhong Zhang +4
Spatial intelligence is central to embodied cognition, yet contemporary AI systems still struggle to reason about physical interactions in open-world human environments. Despite st…
PFDepth: Heterogeneous Pinhole-Fisheye Joint Depth Estimation via Distortion-aware Gaussian-Splatted Volumetric Fusion
Zhiwei Zhang, Ruikai Xu, Weijian Zhang +5
In this paper, we present the first pinhole-fisheye framework for heterogeneous multi-view depth estimation, PFDepth. Our key insight is to exploit the complementary characteristic…
T2S: Tokenized Skill Scaling for Lifelong Imitation Learning
Hongquan Zhang, Jingyu Gong, Zhizhong Zhang +3
The main challenge in lifelong imitation learning lies in the balance between mitigating catastrophic forgetting of previous skills while maintaining sufficient capacity for acquir…
NaviMaster: Learning a Unified Policy for GUI and Embodied Navigation Tasks
Zhihao Luo, Wentao Yan, Jingyu Gong +5
Recent advances in Graphical User Interface (GUI) and embodied navigation have driven progress, yet these domains have largely evolved in isolation, with disparate datasets and tra…
YouTube-Occ: Learning Indoor 3D Semantic Occupancy Prediction from YouTube Videos
Haoming Chen, Lichen Yuan, TianFang Sun +5
3D semantic occupancy prediction is crucial for fine-grained scene understanding, yet its advancement in privacy-sensitive indoor environments is fundamentally hindered by the scar…
DORAEMON: Decentralized Ontology-aware Reliable Agent with Enhanced Memory Oriented Navigation
Tianjun Gu, Linfeng Li, Xuhong Wang +6
Adaptive navigation in unfamiliar environments is crucial for household service robots but remains challenging due to the need for both low-level path planning and high-level scene…
Hydra-MDP++: Advancing End-to-End Driving via Expert-Guided Hydra-Distillation
Kailin Li, Zhenxin Li, Shiyi Lan +6
Hydra-MDP++ introduces a novel teacher-student knowledge distillation framework with a multi-head decoder that learns from human demonstrations and rule-based experts. Using a ligh…
One-for-More: Continual Diffusion Model for Anomaly Detection
Xiaofan Li, Xin Tan, Zhuo Chen +8
With the rise of generative models, there is a growing interest in unifying all tasks within a generative framework. Anomaly detection methods also fall into this scope and utilize…
Diffusion Implicit Policy for Unpaired Scene-aware Motion Synthesis
Jingyu Gong, Chong Zhang, Fengqi Liu +5
Scene-aware motion synthesis has been widely researched recently due to its numerous applications. Prevailing methods rely heavily on paired motion-scene data, while it is difficul…
Large Continual Instruction Assistant
Jingyang Qiao, Zhizhong Zhang, Xin Tan +3
Continual Instruction Tuning (CIT) is adopted to continually instruct Large Models to follow human intent data by data. It is observed that existing gradient update would heavily d…
Exploring the Untouched Sweeps for Conflict-Aware 3D Segmentation Pretraining
Tianfang Sun, Zhizhong Zhang, Xin Tan +2
LiDAR-camera 3D representation pretraining has shown significant promise for 3D perception tasks and related applications. However, two issues widely exist in this framework: 1) So…
Harmonizing Visual Text Comprehension and Generation
Zhen Zhao, Jingqun Tang, Binghong Wu +7
In this work, we present TextHarmony, a unified and versatile multimodal generative model proficient in comprehending and generating visual text. Simultaneously generating images a…
Building a Strong Pre-Training Baseline for Universal 3D Large-Scale Perception
Haoming Chen, Zhizhong Zhang, Yanyun Qu +3
An effective pre-training framework with universal 3D representations is extremely desired in perceiving large-scale dynamic scenes. However, establishing such an ideal framework t…
Gradient Projection For Continual Parameter-Efficient Tuning
Jingyang Qiao, Zhizhong Zhang, Xin Tan +4
Parameter-efficient tunings (PETs) have demonstrated impressive performance and promising perspectives in training large models, while they are still confronted with a common probl…