activity
20192026
most citedRMIX: Learning Risk-Sensitive Policies for Cooperative Reinforcement Learning Agents

16 citations · 65 across the 48 of their papers we have counts for

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Showing 2026Show all

5 papers · 1 filter

cs.LG2026

SceneSelect: Selective Learning for Trajectory Scene Classification and Expert Scheduling

Xinrun Wang, Deshun Xia, Yuxi Sun +1

Accurate trajectory prediction is fundamentally challenging due to high scene heterogeneity - the severe variance in motion velocity, spatial density, and interaction patterns acro…

cs.AI2026

The Agent Use of Agent Beings: Agent Cybernetics Is the Missing Science of Foundation Agents

Xinrun Wang, Chang Yang, He Zhao +2

LLM-based foundation agents that perceive, reason, and act across thousands of reasoning steps are rapidly becoming the dominant paradigm for deploying artificial intelligence in o…

cs.AI2026

Graph-based Agent Memory: Taxonomy, Techniques, and Applications

Chang Yang, Chuang Zhou, Yilin Xiao +15

Memory emerges as the core module in the Large Language Model (LLM)-based agents for long-horizon complex tasks (e.g., multi-turn dialogue, game playing, scientific discovery), whe…

cs.AI2026

History Is Not Enough: An Adaptive Dataflow System for Financial Time-Series Synthesis

Haochong Xia, Yao Long Teng, Regan Tan +3

In quantitative finance, the gap between training and real-world performance-driven by concept drift and distributional non-stationarity-remains a critical obstacle for building re…

cs.AI2026

SCALER:Synthetic Scalable Adaptive Learning Environment for Reasoning

Caijun Xu, Changyi Xiao, Zhongyuan Peng +2

Reinforcement learning (RL) offers a principled way to enhance the reasoning capabilities of large language models, yet its effectiveness hinges on training signals that remain inf…