Autonomous agents, tool use, and agentic systems
![[2603.10062] Multi-Agent Memory from a Computer Architecture Perspective: Visions and Challenges Ahead](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
Abstract page for arXiv paper 2603.10062: Multi-Agent Memory from a Computer Architecture Perspective: Visions and Challenges Ahead
Abstract page for arXiv paper 2601.19066: Dynamic Cogeneration of Bug Reproduction Test in Agentic Program Repair
Abstract page for arXiv paper 2510.16187: Zero-Shot Coordination in Ad Hoc Teams with Generalized Policy Improvement and Difference Rewards
The paper presents EpidemIQs, a multi-agent framework utilizing large language models for efficient epidemic modeling, demonstrating impr...
This article explores the concept of Grounding IDs, which are latent identifiers that enhance multimodal binding in large vision-language...
This article explores the foundational bottlenecks in multimodal reasoning, highlighting how additional modalities can enhance or hinder ...
The EO-1 model is introduced as a unified foundation for general robot control, enhancing multimodal reasoning through a large dataset an...
The paper introduces ClearFairy, an AI assistant designed to enhance decision-making in creative workflows by structuring reasoning and i...
The paper presents CASCADE, a novel LLM-powered JavaScript deobfuscator developed by Google, which enhances code comprehension and analys...
The paper presents LeanPremise, a neural premise selection system that enhances LeanHammer, a tool for automated reasoning in proof assis...
The paper presents Knowledgeable-R1, a reinforcement-learning framework designed to enhance retrieval-augmented generation (RAG) by mitig...
The paper presents PROGRESS, a framework for prioritized concept learning in vision-language models, enabling efficient sample selection ...
The paper presents QCS-ADME, a novel quantum circuit search framework for predicting drug properties, addressing challenges in imbalanced...
The paper 'Renaissance' explores the pretraining of vision-language encoders, addressing best practices and introducing a flexible evalua...
This article presents a novel framework for managing transportation infrastructure using multi-agent deep reinforcement learning, address...
The paper discusses advancements in AI towards ultra-long-horizon autonomy, introducing ML-Master 2.0, which utilizes Hierarchical Cognit...
The paper introduces KeplerAgent, a physics-guided LLM framework designed for symbolic equation discovery, enhancing accuracy and robustn...
The paper presents a novel framework for part retrieval in 3D CAD assemblies using vision-language models, emphasizing training-free meth...
The paper presents a multi-agent framework to enhance contextual privacy in large language models (LLMs), demonstrating a significant red...
The paper presents InsightX Agent, an LMM-based framework that enhances X-ray non-destructive testing (NDT) by improving reliability, int...
The paper presents Med-REFL, a framework designed to enhance medical reasoning in AI by enabling self-correction through fine-grained ref...
The paper explores the impact of spurious rewards in reinforcement learning with verifiable rewards (RLVR), demonstrating how they can en...
The paper presents GraftLLM, a novel method for knowledge fusion in large language models using modular SkillPacks, enhancing cross-capab...
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