1 citations · 1 across the 6 of their papers we have counts for
6 papers
State Rank Dynamics in Linear Attention LLMs
Ao Sun, Hongtao Zhang, Heng Zhou +9
Linear Attention Large Language Models (LLMs) offer a compelling recurrent formulation that compresses context into a fixed-size state matrix, enabling constant-time inference. How…
LTS-VoiceAgent: A Listen-Think-Speak Framework for Efficient Streaming Voice Interaction via Semantic Triggering and Incremental Reasoning
Wenhao Zou, Yuwei Miao, Zhanyu Ma +5
Real-time voice agents face a dilemma: end-to-end models often lack deep reasoning, while cascaded pipelines incur high latency by executing ASR, LLM reasoning, and TTS strictly in…
Long-term Task-oriented Agent: Proactive Long-term Intent Maintenance in Dynamic Environments
Qinglong Shi, Donghai Wang, Hantao Zhou +5
Current large language model agents predominantly operate under a reactive paradigm, responding only to immediate user queries within short-term sessions. This limitation hinders t…
Efficient Paths and Dense Rewards: Probabilistic Flow Reasoning for Large Language Models
Yan Liu, Feng Zhang, Zhanyu Ma +6
High-quality chain-of-thought has demonstrated strong potential for unlocking the reasoning capabilities of large language models. However, current paradigms typically treat the re…
UserLM-R1: Modeling Human Reasoning in User Language Models with Multi-Reward Reinforcement Learning
Feng Zhang, Shijia Li, Chunmao Zhang +7
User simulators serve as the critical interactive environment for agent post-training, and an ideal user simulator generalizes across domains and proactively engages in negotiation…
Fine-Mem: Fine-Grained Feedback Alignment for Long-Horizon Memory Management
Weitao Ma, Xiaocheng Feng, Lei Huang +7
Effective memory management is essential for large language model agents to navigate long-horizon tasks. Recent research has explored using Reinforcement Learning to develop specia…