1 citations · 2 across the 10 of their papers we have counts for
10 papers
Logic-Regularized Verifier Elicits Reasoning from LLMs
Xinyu Wang, Changzhi Sun, Lian Cheng +4
Verifiers are crucial components for enhancing modern LLMs' reasoning capability. Typicalverifiers require resource-intensive superviseddataset construction, which is costly and fa…
TeleMem: Building Long-Term and Multimodal Memory for Agentic AI
Chunliang Chen, Ming Guan, Xiao Lin +8
Large language models (LLMs) excel at many NLP tasks but struggle to sustain long-term interactions due to limited attention over extended dialogue histories. Retrieval-augmented g…
Beyond Heuristics: A Decision-Theoretic Framework for Agent Memory Management
Changzhi Sun, Xiangyu Chen, Jixiang Luo +2
External memory is a key component of modern large language model (LLM) systems, enabling long-term interaction and personalization. Despite its importance, memory management is st…
Gestura: A LVLM-Powered System Bridging Motion and Semantics for Real-Time Free-Form Gesture Understanding
Zhuoming Li, Aitong Liu, Mengxi Jia +5
Free-form gesture understanding is highly appealing for human-computer interaction, as it liberates users from the constraints of predefined gesture categories. However, the sole e…
EV-NVC: Efficient Variable bitrate Neural Video Compression
Yongcun Hu, Yingzhen Zhai, Jixiang Luo +4
Training neural video codec (NVC) with variable rate is a highly challenging task due to its complex training strategies and model structure. In this paper, we train an efficient v…
TeleEgo: Benchmarking Egocentric AI Assistants in the Wild
Jiaqi Yan, Ruilong Ren, Jingren Liu +13
Egocentric AI assistants in real-world settings must process multi-modal inputs (video, audio, text), respond in real time, and retain evolving long-term memory. However, existing…
Mixture of Noise for Pre-Trained Model-Based Class-Incremental Learning
Kai Jiang, Zhengyan Shi, Dell Zhang +2
Class Incremental Learning (CIL) aims to continuously learn new categories while retaining the knowledge of old ones. Pre-trained models (PTMs) show promising capabilities in CIL.…
Infinite Video Understanding
Dell Zhang, Xiangyu Chen, Jixiang Luo +6
The rapid advancements in Large Language Models (LLMs) and their multimodal extensions (MLLMs) have ushered in remarkable progress in video understanding. However, a fundamental ch…
Decoupling the Image Perception and Multimodal Reasoning for Reasoning Segmentation with Digital Twin Representations
Yizhen Li, Dell Zhang, Xuelong Li +1
Reasoning Segmentation (RS) is a multimodal vision-text task that requires segmenting objects based on implicit text queries, demanding both precise visual perception and vision-te…
SmartFreeEdit: Mask-Free Spatial-Aware Image Editing with Complex Instruction Understanding
Qianqian Sun, Jixiang Luo, Dell Zhang +1
Recent advancements in image editing have utilized large-scale multimodal models to enable intuitive, natural instruction-driven interactions. However, conventional methods still f…