Heterogeneity in Multi-Agent Reinforcement Learning
arXiv:2512.22941v1 Announce Type: cross Abstract: Heterogeneity is a fundamental property in multi-agent reinforcement learning (MARL), which is closely related not…
Learning Evolving Latent Strategies for Multi-Agent Language Systems without Model Fine-Tuning
arXiv:2512.20629v2 Announce Type: replace-cross Abstract: This study proposes a multi-agent language framework that enables continual strategy evolution without fine-tuning the…
From Visual Perception to Deep Empathy: An Automated Assessment Framework for House-Tree-Person Drawings Using Multimodal LLMs and Multi-Agent Collaboration
arXiv:2512.21360v1 Announce Type: new Abstract: Background: The House-Tree-Person (HTP) drawing test, introduced by John Buck in 1948, remains a widely…
One Tool Is Enough: Reinforcement Learning for Repository-Level LLM Agents
arXiv:2512.20957v2 Announce Type: replace-cross Abstract: Locating the files and functions requiring modification in large open-source software (OSS) repositories is challenging…
MMCTOP: A Multimodal Textualization and Mixture-of-Experts Framework for Clinical Trial Outcome Prediction
arXiv:2512.21897v1 Announce Type: cross Abstract: Addressing the challenge of multimodal data fusion in high-dimensional biomedical informatics, we propose MMCTOP, a…
Aerial World Model for Long-horizon Visual Generation and Navigation in 3D Space
arXiv:2512.21887v1 Announce Type: cross Abstract: Unmanned aerial vehicles (UAVs) have emerged as powerful embodied agents. One of the core abilities…
TableGPT-R1: Advancing Tabular Reasoning Through Reinforcement Learning
arXiv:2512.20312v2 Announce Type: replace-cross Abstract: Tabular data serves as the backbone of modern data analysis and scientific research. While Large…
Generalised Linear Models in Deep Bayesian RL with Learnable Basis Functions
arXiv:2512.20974v1 Announce Type: cross Abstract: Bayesian Reinforcement Learning (BRL) provides a framework for generalisation of Reinforcement Learning (RL) problems from…
GenTSE: Enhancing Target Speaker Extraction via a Coarse-to-Fine Generative Language Model
arXiv:2512.20978v1 Announce Type: cross Abstract: Language Model (LM)-based generative modeling has emerged as a promising direction for TSE, offering potential…
Anatomy-R1: Enhancing Anatomy Reasoning in Multimodal Large Language Models via Anatomical Similarity Curriculum and Group Diversity Augmentation
arXiv:2512.19512v2 Announce Type: replace-cross Abstract: Multimodal Large Language Models (MLLMs) have achieved impressive progress in natural image reasoning, yet their…