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Deep Academic Survey: Stateful Agentic Closed-Loop Paradigm for Academic Survey Automation
Zhikai Xu, Zhucun Xue, Teng Hu +3
Academic surveys play a central role in organizing rapidly expanding scholarly literature, yet their construction requires extensive paper analysis, coherent knowledge organization…
Improving General Role-Playing Agents via Psychology-Grounded Reasoning and Role-Aware Policy Optimization
Zhenhua Xu, Dongsheng Chen, Jian Li +7
Building general-purpose role-playing agents that faithfully portray any character from a natural-language profile remains challenging. The dominant paradigm -- supervised fine-tun…
Summarization is Not Dead Yet
Dongqi Liu, Chenxi Whitehouse, Zheng Zhao +3
The progress of large language models (LLMs) has fueled claims that model-generated summaries rival or even surpass human-written references, raising questions about whether summar…
PixVerve: Advancing Native UHR Image Generation to 100MP with a Large-Scale High-Quality Dataset
Haojun Chen, Haoyang He, Chengming Xu +11
Text-to-Image (T2I) models have recently seen notable progress around 1K and 2K resolution. With the extreme desire for better visual experience and the rapid development of imagin…
Advancing Narrative Long Video Generation via Training-Free Identity-Aware Memory
Jinzhuo Liu, Jiangning Zhang, Wencan Jiang +5
Autoregressive video generation has improved rapidly in visual fidelity and interactivity, but it still suffers from long-term inconsistency and memory degradation. Most existing s…
Omni-Customizer: End-to-End MultiModal Customization for Joint Audio-Video Generation
Yuheng Chen, Qingdong He, Teng Hu +4
The landscape of joint audio and video generation has been fundamentally transformed by the advent of powerful foundation models. Despite these strides, achieving cohesive multimod…
Evolution of Optimization Methods: Algorithms, Scenarios, and Evaluations
Tong Zhang, Jiangning Zhang, Zhucun Xue +9
Balancing convergence speed, generalization capability, and computational efficiency remains a core challenge in deep learning optimization. First-order gradient descent methods, e…
Improving Search Agent with One Line of Code
Jian Li, Dongsheng Chen, Zhenhua Xu +5
Tool-based Agentic Reinforcement Learning (TARL) has emerged as a promising paradigm for training search agents to interact with external tools for a multi-turn information-seeking…
SE-Search: Self-Evolving Search Agent via Memory and Dense Reward
Jian Li, Yizhang Jin, Dongqi Liu +9
Retrieval augmented generation (RAG) reduces hallucinations and factual errors in large language models (LLMs) by conditioning generation on retrieved external knowledge. Recent se…
AdaMARP: An Adaptive Multi-Agent Interaction Framework for General Immersive Role-Playing
Zhenhua Xu, Dongsheng Chen, Shuo Wang +4
LLM role-playing aims to portray arbitrary characters in interactive narratives, yet existing systems often suffer from limited immersion and adaptability. They typically under-mod…
Disco-RAG: Discourse-Aware Retrieval-Augmented Generation
Dongqi Liu, Hang Ding, Qiming Feng +6
Retrieval-Augmented Generation (RAG) has emerged as an important means of enhancing the performance of large language models (LLMs) in knowledge-intensive tasks. However, most exis…