1 citations · 3 across the 5 of their papers we have counts for
6 papers
Hy-Memory-30B-A3B: Attributed Reinforcement Learning for Long-Term Memory Writing
Tianxiang Fei, Jiazheng Kang, Mao Zheng +2
External-memory systems extend language-model applications beyond a context window, but their quality depends critically on the model executing the write path: deciding what to ret…
Towards Root Memory: Benchmarking and Enhancing Implicit Logical Memory Retrieval for Personalized LLMs
Hongxun Ding, Xiang Yu, Chengbing Wang +4
Memory systems are essential for personalized Large Language Models (LLMs). However, retrieval within these systems primarily relies on semantic similarity, potentially missing log…
Memory Beyond Recall: A Dual-Process Cognitive Memory System for Self-Evolving LLM Agents
Tianxiang Fei, Mingyang Song, Mao Zheng +1
Long-term memory for an LLM agent is more than retrieving the right passage at the right time. Current memory systems collapse belief revision, causal coupling, and cross-domain ab…
AlpsBench: An LLM Personalization Benchmark for Real-Dialogue Memorization and Preference Alignment
Jianfei Xiao, Xiang Yu, Chengbing Wang +8
As Large Language Models (LLMs) evolve into lifelong AI assistants, LLM personalization has become a critical frontier. However, progress is currently bottlenecked by the absence o…
Seed1.5-Thinking: Advancing Superb Reasoning Models with Reinforcement Learning
ByteDance Seed, :, Jiaze Chen +267
We introduce Seed1.5-Thinking, capable of reasoning through thinking before responding, resulting in improved performance on a wide range of benchmarks. Seed1.5-Thinking achieves 8…
VAPO: Efficient and Reliable Reinforcement Learning for Advanced Reasoning Tasks
Yu Yue, Yufeng Yuan, Qiying Yu +24
We present VAPO, Value-based Augmented Proximal Policy Optimization framework for reasoning models., a novel framework tailored for reasoning models within the value-based paradigm…