14 papers
KVEraser: Learning to Steer KV Cache for Efficient Localized Context Erasing
Mufei Li, Shikun Liu, Dongqi Fu +5
Post-hoc context erasing over the KV cache is challenging because a local edit has a global consequence: once a span has been processed, its influence propagates into the cached st…
Towards Direct Latent-Space Synthesis for Parallel Branches in LLM-Agent Workflows
Shikun Liu, Mufei Li, Dongqi Fu +5
Large language models increasingly serve as execution engines for agentic systems, yet they still consume context through a sequential text interface. This creates a mismatch with…
On Information Self-Locking in Reinforcement Learning for Active Reasoning of LLM agents
Deyu Zou, Yongqiang Chen, Fan Feng +4
Reinforcement learning (RL) has become a de facto paradigm for building LLM-based agents that act, interact, and reason over extended task horizons. However, in active reasoning wh…
Can LLM Agents Simulate Dynamic Networks? A Case Study on Email Networks with Phishing Synthesis
Siqi Miao, Ziyang Chen, Yuhong Luo +4
While Large Language Model (LLM) multi-agent systems (MAS) offer a transformative approach to simulating human behavior in complex systems, it remains largely unexplored whether th…
Reducing Belief Deviation in Reinforcement Learning for Active Reasoning
Deyu Zou, Yongqiang Chen, Jianxiang Wang +5
Active reasoning requires large language model (LLM) agents to interact with external sources and strategically gather information to solve problems in multiple turns. Central to t…
Measuring Physical-World Privacy Awareness of Large Language Models: An Evaluation Benchmark
Xinjie Shen, Mufei Li, Pan Li
The deployment of Large Language Models (LLMs) in embodied agents creates an urgent need to measure their privacy awareness in the physical world. Existing evaluation methods, howe…