4 citations · 8 across the 37 of their papers we have counts for
14 papers · 1 filter
Dual Knowledge-Enhanced Two-Stage Reasoner for Multimodal Dialog Systems
Xiaolin Chen, Xuemeng Song, Haokun Wen +3
Textual response generation is pivotal for multimodal \mbox{task-oriented} dialog systems, which aims to generate proper textual responses based on the multimodal context. While ex…
PUMA: Layer-Pruned Language Model for Efficient Unified Multimodal Retrieval with Modality-Adaptive Learning
Yibo Lyu, Rui Shao, Gongwei Chen +3
As multimedia content expands, the demand for unified multimodal retrieval (UMR) in real-world applications increases. Recent work leverages multimodal large language models (MLLMs…
Technical Report for Ego4D Long-Term Action Anticipation Challenge 2025
Qiaohui Chu, Haoyu Zhang, Yisen Feng +4
In this report, we present a novel three-stage framework developed for the Ego4D Long-Term Action Anticipation (LTA) task. Inspired by recent advances in foundation models, our met…
SplitLoRA: Balancing Stability and Plasticity in Continual Learning Through Gradient Space Splitting
Haomiao Qiu, Miao Zhang, Ziyue Qiao +3
Continual Learning requires a model to learn multiple tasks in sequence while maintaining both stability:preserving knowledge from previously learned tasks, and plasticity:effectiv…
OSGNet @ Ego4D Episodic Memory Challenge 2025
Yisen Feng, Haoyu Zhang, Qiaohui Chu +4
In this report, we present our champion solutions for the three egocentric video localization tracks of the Ego4D Episodic Memory Challenge at CVPR 2025. All tracks require precise…
Boost Post-Training Quantization via Null Space Optimization for Large Language Models
Jiaqi Zhao, Miao Zhang, Deng Xiang +3
Existing post-training quantization methods for large language models (LLMs) offer remarkable success. However, the increasingly marginal performance gains suggest that existing qu…
Optimus-3: Dual-Router Aligned Mixture-of-Experts Agent with Dual-Granularity Reasoning-Aware Policy Optimization
Zaijing Li, Yuquan Xie, Rui Shao +5
Developing generalist agents capable of solving open-ended tasks in visually rich, dynamic environments remains a core pursuit of embodied AI. While Minecraft has emerged as a comp…
Spatial Understanding from Videos: Structured Prompts Meet Simulation Data
Haoyu Zhang, Meng Liu, Zaijing Li +4
Visual-spatial understanding, the ability to infer object relationships and layouts from visual input, is fundamental to downstream tasks such as robotic navigation and embodied in…
HCQA-1.5 @ Ego4D EgoSchema Challenge 2025
Haoyu Zhang, Yisen Feng, Qiaohui Chu +4
In this report, we present the method that achieves third place for Ego4D EgoSchema Challenge in CVPR 2025. To improve the reliability of answer prediction in egocentric video ques…
Object-Shot Enhanced Grounding Network for Egocentric Video
Yisen Feng, Haoyu Zhang, Meng Liu +2
Egocentric video grounding is a crucial task for embodied intelligence applications, distinct from exocentric video moment localization. Existing methods primarily focus on the dis…
Handling Imbalanced Pseudolabels for Vision-Language Models with Concept Alignment and Confusion-Aware Calibrated Margin
Yuchen Wang, Xuefeng Bai, Xiucheng Li +3
Adapting vision-language models (VLMs) to downstream tasks with pseudolabels has gained increasing attention. A major obstacle is that the pseudolabels generated by VLMs tend to be…
Embodied Crowd Counting
Runling Long, Yunlong Wang, Jia Wan +5
Occlusion is one of the fundamental challenges in crowd counting. In the community, various data-driven approaches have been developed to address this issue, yet their effectivenes…
PTQ1.61: Push the Real Limit of Extremely Low-Bit Post-Training Quantization Methods for Large Language Models
Jiaqi Zhao, Miao Zhang, Ming Wang +5
Large Language Models (LLMs) suffer severe performance degradation when facing extremely low-bit (sub 2-bit) quantization. Several existing sub 2-bit post-training quantization (PT…
FALCON: Resolving Visual Redundancy and Fragmentation in High-resolution Multimodal Large Language Models via Visual Registers
Renshan Zhang, Rui Shao, Gongwei Chen +4
The incorporation of high-resolution visual input equips multimodal large language models (MLLMs) with enhanced visual perception capabilities for real-world tasks. However, most e…