| 2025-01-01 |
MASTER: Enhancing Large Language Model via Multi-Agent Simulated Teaching |
NeurIPS 2025 |
— |
| 2025-01-01 |
Multi-Agent Imitation by Learning and Sampling from Factorized Soft Q-Function |
NeurIPS 2025 |
— |
| 2025-01-01 |
MoodAngels: A Retrieval-augmented Multi-agent Framework for Psychiatry Diagnosis |
NeurIPS 2025 |
— |
| 2025-01-01 |
MAGNET: A Multi-agent Framework for Finding Audio-Visual Needles by Reasoning over Multi-Video Haystacks |
NeurIPS 2025 |
— |
| 2025-01-01 |
AI-Researcher: Autonomous Scientific Innovation |
NeurIPS 2025 |
— |
| 2025-01-01 |
Multi-Agent Reinforcement Learning with Communication-Constrained Priors |
NeurIPS 2025 |
— |
| 2025-01-01 |
AutoRedTeamer: Autonomous Red Teaming with Lifelong Attack Integration |
NeurIPS 2025 |
— |
| 2025-01-01 |
WebDancer: Towards Autonomous Information Seeking Agency |
NeurIPS 2025 |
— |
| 2025-01-01 |
MisoDICE: Multi-Agent Imitation from Mixed-Quality Demonstrations |
NeurIPS 2025 |
— |
| 2025-01-01 |
Are Large Language Models Sensitive to the Motives Behind Communication? |
NeurIPS 2025 |
— |
| 2025-01-01 |
Learning “Partner-Aware” Collaborators in Multi-Party Collaboration |
NeurIPS 2025 |
— |
| 2025-01-01 |
Fair Cooperation in Mixed-Motive Games via Conflict-Aware Gradient Adjustment |
NeurIPS 2025 |
— |
| 2025-01-01 |
Many LLMs Are More Utilitarian Than One |
NeurIPS 2025 |
— |
| 2025-01-01 |
Collaborative Reasoner: Self-Improving Social Agents with Synthetic Conversations |
NeurIPS 2025 |
— |
| 2025-01-01 |
Generative Caching for Structurally Similar Prompts and Responses |
NeurIPS 2025 |
— |
| 2025-01-01 |
TRAP: Targeted Redirecting of Agentic Preferences |
NeurIPS 2025 |
— |
| 2025-01-01 |
Robust and Diverse Multi-Agent Learning via Rational Policy Gradient |
NeurIPS 2025 |
— |
| 2025-01-01 |
SpecMAS: A Multi-Agent System for Self-Verifying System Generation via Formal Model Checking |
NeurIPS 2025 |
— |
| 2025-01-01 |
Evaluating LLMs in Open-Source Games |
NeurIPS 2025 |
— |
| 2025-01-01 |
Policy Gradient Methods Converge Globally in Imperfect-Information Extensive-Form Games |
NeurIPS 2025 |
— |
| 2025-01-01 |
Solving Continuous Mean Field Games: Deep Reinforcement Learning for Non-Stationary Dynamics |
NeurIPS 2025 |
— |
| 2025-01-01 |
Scalable Neural Incentive Design with Parameterized Mean-Field Approximation |
NeurIPS 2025 |
— |
| 2025-01-01 |
Cooperative Bargaining Games Without Utilities: Mediated Solutions from Direction Oracles |
NeurIPS 2025 |
— |
| 2025-01-01 |
How to Train Your LLM Web Agent: A Statistical Diagnosis |
NeurIPS 2025 |
— |
| 2025-01-01 |
A-Mem: Agentic Memory for LLM Agents |
NeurIPS 2025 |
— |
| 2025-01-01 |
Multi-Agent Learning under Uncertainty: Recurrence vs. Concentration |
NeurIPS 2025 |
— |
| 2025-01-01 |
Planning with Quantized Opponent Models |
NeurIPS 2025 |
— |
| 2025-01-01 |
MALinZero: Efficient Low-Dimensional Search for Mastering Complex Multi-Agent Planning |
NeurIPS 2025 |
— |
| 2025-01-01 |
Utility Engineering: Analyzing and Controlling Emergent Value Systems in AIs |
NeurIPS 2025 |
— |
| 2025-01-01 |
LOPT: Learning Optimal Pigovian Tax in Sequential Social Dilemmas |
NeurIPS 2025 |
— |
| 2025-01-01 |
Social World Model-Augmented Mechanism Design Policy Learning |
NeurIPS 2025 |
— |
| 2025-01-01 |
InstructFlow: Adaptive Symbolic Constraint-Guided Code Generation for Long-Horizon Planning |
NeurIPS 2025 |
— |
| 2025-01-01 |
TrajAgent: An LLM-Agent Framework for Trajectory Modeling via Large-and-Small Model Collaboration |
NeurIPS 2025 |
— |
| 2025-01-01 |
Planning without Search: Refining Frontier LLMs with Offline Goal-Conditioned RL |
NeurIPS 2025 |
— |
| 2025-01-01 |
Retro-R1: LLM-based Agentic Retrosynthesis |
NeurIPS 2025 |
— |
| 2025-01-01 |
Breaking the Performance Ceiling in Reinforcement Learning requires Inference Strategies |
NeurIPS 2025 |
— |
| 2025-01-01 |
Seeing through Uncertainty: Robust Task-Oriented Optimization in Visual Navigation |
NeurIPS 2025 |
— |
| 2025-01-01 |
SYMPHONY: Synergistic Multi-agent Planning with Heterogeneous Language Model Assembly |
NeurIPS 2025 |
— |
| 2025-01-01 |
DRIFT: Dynamic Rule-Based Defense with Injection Isolation for Securing LLM Agents |
NeurIPS 2025 |
— |
| 2025-01-01 |
SE-Agent: Self-Evolution Trajectory Optimization in Multi-Step Reasoning with LLM-Based Agents |
NeurIPS 2025 |
— |
| 2025-01-01 |
OrbitZoo: Real Orbital Systems Challenges for Reinforcement Learning |
NeurIPS 2025 |
— |
| 2025-01-01 |
DyFlow: Dynamic Workflow Framework for Agentic Reasoning |
NeurIPS 2025 |
— |
| 2025-01-01 |
Oryx: a Scalable Sequence Model for Many-Agent Coordination in Offline MARL |
NeurIPS 2025 |
— |
| 2025-01-01 |
Among Us: A Sandbox for Measuring and Detecting Agentic Deception |
NeurIPS 2025 |
— |
| 2025-01-01 |
Certifying Deep Network Risks and Individual Predictions with PAC-Bayes Loss via Localized Priors |
NeurIPS 2025 |
— |
| 2025-01-01 |
Wonder Wins Ways: Curiosity-Driven Exploration through Multi-Agent Contextual Calibration |
NeurIPS 2025 |
— |
| 2025-01-01 |
Automated Model Discovery via Multi-modal & Multi-step Pipeline |
NeurIPS 2025 |
— |
| 2025-01-01 |
OWL: Optimized Workforce Learning for General Multi-Agent Assistance in Real-World Task Automation |
NeurIPS 2025 |
— |
| 2025-01-01 |
LILO: Learning to Reason at the Frontier of Learnability |
NeurIPS 2025 |
— |
| 2025-01-01 |
SketchMind: A Multi-Agent Cognitive Framework for Assessing Student-Drawn Scientific Sketches |
NeurIPS 2025 |
— |
| 2025-01-01 |
PARCO: Parallel AutoRegressive Models for Multi-Agent Combinatorial Optimization |
NeurIPS 2025 |
— |
| 2025-01-01 |
Process vs. Outcome Reward: Which is Better for Agentic RAG Reinforcement Learning |
NeurIPS 2025 |
— |
| 2025-01-01 |
STRATUS: A Multi-agent System for Autonomous Reliability Engineering of Modern Clouds |
NeurIPS 2025 |
— |
| 2025-01-01 |
Revisiting Multi-Agent World Modeling from a Diffusion-Inspired Perspective |
NeurIPS 2025 |
— |
| 2025-01-01 |
Distilling LLM Agent into Small Models with Retrieval and Code Tools |
NeurIPS 2025 |
— |
| 2025-01-01 |
VAGEN: Reinforcing World Model Reasoning for Multi-Turn VLM Agents |
NeurIPS 2025 |
— |
| 2025-01-01 |
From Replication to Redesign: Exploring Pairwise Comparisons for LLM-Based Peer Review |
NeurIPS 2025 |
— |
| 2025-01-01 |
MACS: Multi-Agent Reinforcement Learning for Optimization of Crystal Structures |
NeurIPS 2025 |
— |
| 2025-01-01 |
SiriuS: Self-improving Multi-agent Systems via Bootstrapped Reasoning |
NeurIPS 2025 |
— |
| 2025-01-01 |
SEC-bench: Automated Benchmarking of LLM Agents on Real-World Software Security Tasks |
NeurIPS 2025 |
— |
| 2025-01-01 |
Thinking vs. Doing: Improving Agent Reasoning by Scaling Test-Time Interaction |
NeurIPS 2025 |
— |
| 2025-01-01 |
ReMA: Learning to Meta-Think for LLMs with Multi-agent Reinforcement Learning |
NeurIPS 2025 |
— |
| 2025-01-01 |
Agentic Plan Caching: Test-Time Memory for Fast and Cost-Efficient LLM Agents |
NeurIPS 2025 |
— |
| 2025-01-01 |
TAI3: Testing Agent Integrity in Interpreting User Intent |
NeurIPS 2025 |
— |
| 2025-01-01 |
Stackelberg Learning with Outcome-based Payment |
NeurIPS 2025 |
— |
| 2025-01-01 |
High-order Interactions Modeling for Interpretable Multi-Agent Q-Learning |
NeurIPS 2025 |
— |
| 2025-01-01 |
Role-aware Multi-agent Reinforcement Learning for Coordinated Emergency Traffic Control |
NeurIPS 2025 |
— |
| 2025-01-01 |
SimWorld: An Open-ended Simulator for Agents in Physical and Social Worlds |
NeurIPS 2025 |
— |
| 2025-01-01 |
Heterogeneous Graph Transformers for Simultaneous Mobile Multi-Robot Task Allocation and Scheduling under Temporal Constraints |
NeurIPS 2025 |
— |
| 2025-01-01 |
SimWorld-Robotics: Synthesizing Photorealistic and Dynamic Urban Environments for Multimodal Robot Navigation and Collaboration |
NeurIPS 2025 |
— |
| 2025-01-01 |
Automated Composition of Agents: A Knapsack Approach for Agentic Component Selection |
NeurIPS 2025 |
— |
| 2025-01-01 |
4KAgent: Agentic Any Image to 4K Super-Resolution |
NeurIPS 2025 |
— |
| 2025-01-01 |
LLM Strategic Reasoning: Agentic Study through Behavioral Game Theory |
NeurIPS 2025 |
— |
| 2025-01-01 |
HMARL-CBF – Hierarchical Multi-Agent Reinforcement Learning with Control Barrier Functions for Safety-Critical Autonomous Systems |
NeurIPS 2025 |
— |
| 2025-01-01 |
Eliciting Reasoning in Language Models with Cognitive Tools |
NeurIPS 2025 |
— |
| 2025-01-01 |
Shapley-Coop: Credit Assignment for Emergent Cooperation in Self-Interested LLM Agents |
NeurIPS 2025 |
— |
| 2025-01-01 |
Hogwild! Inference: Parallel LLM Generation via Concurrent Attention |
NeurIPS 2025 |
— |
| 2025-01-01 |
Distributed Multi-Agent Bandits Over Erdős-Rényi Random Networks |
NeurIPS 2025 |
— |
| 2025-01-01 |
GauDP: Reinventing Multi-Agent Collaboration through Gaussian-Image Synergy in Diffusion Policies |
NeurIPS 2025 |
— |
| 2025-01-01 |
Belief-Calibrated Multi-Agent Consensus Seeking for Complex NLP Tasks |
NeurIPS 2025 |
— |
| 2025-01-01 |
Memory Injection Attacks on LLM Agents via Query-Only Interaction |
NeurIPS 2025 |
— |
| 2025-01-01 |
Continuous Soft Actor-Critic: An Off-Policy Learning Method Robust to Time Discretization |
NeurIPS 2025 |
— |
| 2025-01-01 |
Sequential Multi-Agent Dynamic Algorithm Configuration |
NeurIPS 2025 |
— |
| 2025-01-01 |
Encouraging metric-aware diversity in contrastive representation space |
NeurIPS 2025 |
— |
| 2025-01-01 |
UniMotion: A Unified Motion Framework for Simulation, Prediction and Planning |
NeurIPS 2025 |
— |
| 2025-01-01 |
Contextual Integrity in LLMs via Reasoning and Reinforcement Learning |
NeurIPS 2025 |
— |
| 2025-01-01 |
Think or Not? Selective Reasoning via Reinforcement Learning for Vision-Language Models |
NeurIPS 2025 |
— |
| 2025-01-01 |
Adaptive Context Length Optimization with Low-Frequency Truncation for Multi-Agent Reinforcement Learning |
NeurIPS 2025 |
— |
| 2025-01-01 |
Enhancing LLM Planning for Robotics Manipulation through Hierarchical Procedural Knowledge Graphs |
NeurIPS 2025 |
— |
| 2025-01-01 |
Agents Robust to Distribution Shifts Learn Causal World Models Even Under Mediation |
NeurIPS 2025 |
— |
| 2025-01-01 |
Abstract Counterfactuals for Language Model Agents |
NeurIPS 2025 |
— |
| 2025-01-01 |
KVFlow: Efficient Prefix Caching for Accelerating LLM-Based Multi-Agent Workflows |
NeurIPS 2025 |
— |
| 2025-01-01 |
Ground-Compose-Reinforce: Grounding Language in Agentic Behaviours using Limited Data |
NeurIPS 2025 |
— |
| 2025-01-01 |
Self-Generated In-Context Examples Improve LLM Agents for Sequential Decision-Making Tasks |
NeurIPS 2025 |
— |
| 2025-01-01 |
Privacy Reasoning in Ambiguous Contexts |
NeurIPS 2025 |
— |
| 2025-01-01 |
Learning Equilibria from Data: Provably Efficient Multi-Agent Imitation Learning |
NeurIPS 2025 |
— |
| 2025-01-01 |
HypRL: Reinforcement Learning of Control Policies for Hyperproperties |
NeurIPS 2025 |
— |
| 2025-01-01 |
Intrinsic Goals for Autonomous Agents: Model-Based Exploration in Virtual Zebrafish Predicts Ethological Behavior and Whole-Brain Dynamics |
NeurIPS 2025 |
— |
| 2025-01-01 |
On Feasible Rewards in Multi-Agent Inverse Reinforcement Learning |
NeurIPS 2025 |
— |
| 2025-01-01 |
Regret Lower Bounds for Decentralized Multi-Agent Stochastic Shortest Path Problems |
NeurIPS 2025 |
— |
| 2025-01-01 |
HyperMARL: Adaptive Hypernetworks for Multi-Agent RL |
NeurIPS 2025 |
— |
| 2025-01-01 |
Knowledge Starts with Practice: Knowledge-Aware Exercise Generative Recommendation with Adaptive Multi-Agent Cooperation |
NeurIPS 2025 |
— |
| 2025-01-01 |
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers |
NeurIPS 2025 |
— |
| 2025-01-01 |
Emergent Risk Awareness in Rational Agents under Resource Constraints |
NeurIPS 2025 |
— |
| 2025-01-01 |
Deep Video Discovery: Agentic Search with Tool Use for Long-form Video Understanding |
NeurIPS 2025 |
— |
| 2025-01-01 |
Pragmatic Heterogeneous Collaborative Perception via Generative Communication Mechanism |
NeurIPS 2025 |
— |
| 2025-01-01 |
Towards Principled Unsupervised Multi-Agent Reinforcement Learning |
NeurIPS 2025 |
— |
| 2025-01-01 |
Multi-agent KTO: Enhancing Strategic Interactions of Large Language Model in Language Game |
NeurIPS 2025 |
— |
| 2025-01-01 |
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding |
NeurIPS 2025 |
— |
| 2025-01-01 |
Mechanism Design via the Interim Relaxation |
NeurIPS 2025 |
— |
| 2025-01-01 |
LayerCraft: Enhancing Text-to-Image Generation with CoT Reasoning and Layered Object Integration |
NeurIPS 2025 |
— |
| 2025-01-01 |
A Principle of Targeted Intervention for Multi-Agent Reinforcement Learning |
NeurIPS 2025 |
— |
| 2025-01-01 |
Bayesian Ego-graph Inference for Networked Multi-Agent Reinforcement Learning |
NeurIPS 2025 |
— |
| 2025-01-01 |
AgentBreeder: Mitigating the AI Safety Risks of Multi-Agent Scaffolds via Self-Improvement |
NeurIPS 2025 |
— |
| 2025-01-01 |
VLMLight: Safety-Critical Traffic Signal Control via Vision-Language Meta-Control and Dual-Branch Reasoning Architecture |
NeurIPS 2025 |
— |
| 2025-01-01 |
Rainbow Delay Compensation: A Multi-Agent Reinforcement Learning Framework for Mitigating Observation Delays |
NeurIPS 2025 |
— |
| 2025-01-01 |
Co-Evolving LLM Coder and Unit Tester via Reinforcement Learning |
NeurIPS 2025 |
— |
| 2025-01-01 |
KARMA: Leveraging Multi-Agent LLMs for Automated Knowledge Graph Enrichment |
NeurIPS 2025 |
— |
| 2025-01-01 |
Towards Doctor-Like Reasoning: Medical RAG Fusing Knowledge with Patient Analogy through Textual Gradients |
NeurIPS 2025 |
— |
| 2025-01-01 |
MetaMind: Modeling Human Social Thoughts with Metacognitive Multi-Agent Systems |
NeurIPS 2025 |
— |
| 2025-01-01 |
Attractive Metadata Attack: Inducing LLM Agents to Invoke Malicious Tools |
NeurIPS 2025 |
— |
| 2025-01-01 |
Empirical Study on Robustness and Resilience in Cooperative Multi-Agent Reinforcement Learning |
NeurIPS 2025 |
— |
| 2025-01-01 |
Videos are Sample-Efficient Supervisions: Behavior Cloning from Videos via Latent Representations |
NeurIPS 2025 |
— |
| 2025-01-01 |
RepoMaster: Autonomous Exploration and Understanding of GitHub Repositories for Complex Task Solving |
NeurIPS 2025 |
— |
| 2025-01-01 |
Learning in Stackelberg Mean Field Games: A Non-Asymptotic Analysis |
NeurIPS 2025 |
— |
| 2025-01-01 |
SuffixDecoding: Extreme Speculative Decoding for Emerging AI Applications |
NeurIPS 2025 |
— |
| 2025-01-01 |
Multi-Agent Debate for LLM Judges with Adaptive Stability Detection |
NeurIPS 2025 |
— |
| 2025-01-01 |
GUARDIAN: Safeguarding LLM Multi-Agent Collaborations with Temporal Graph Modeling |
NeurIPS 2025 |
— |
| 2025-01-01 |
Measuring AI Ability to Complete Long Software Tasks |
NeurIPS 2025 |
— |
| 2025-01-01 |
Lessons Learned: A Multi-Agent Framework for Code LLMs to Learn and Improve |
NeurIPS 2025 |
— |
| 2025-01-01 |
Language Modeling by Language Models |
NeurIPS 2025 |
— |
| 2025-01-01 |
Improving Retrieval-Augmented Generation through Multi-Agent Reinforcement Learning |
NeurIPS 2025 |
— |
| 2025-01-01 |
ShapeCraft: LLM Agents for Structured, Textured and Interactive 3D Modeling |
NeurIPS 2025 |
— |
| 2025-01-01 |
ContextAgent: Context-Aware Proactive LLM Agents with Open-world Sensory Perceptions |
NeurIPS 2025 |
— |
| 2025-01-01 |
SceneWeaver: All-in-One 3D Scene Synthesis with an Extensible and Self-Reflective Agent |
NeurIPS 2025 |
— |
| 2025-01-01 |
Bi-Level Knowledge Transfer for Multi-Task Multi-Agent Reinforcement Learning |
NeurIPS 2025 |
— |
| 2025-01-01 |
APOLLO: Automated LLM and Lean Collaboration for Advanced Formal Reasoning |
NeurIPS 2025 |
— |
| 2025-01-01 |
CoP: Agentic Red-teaming for Large Language Models using Composition of Principles |
NeurIPS 2025 |
— |
| 2025-01-01 |
LARGO: Latent Adversarial Reflection through Gradient Optimization for Jailbreaking LLMs |
NeurIPS 2025 |
— |
| 2025-01-01 |
OPHR: Mastering Volatility Trading with Multi-Agent Deep Reinforcement Learning |
NeurIPS 2025 |
— |
| 2025-01-01 |
Conformal Information Pursuit for Interactively Guiding Large Language Models |
NeurIPS 2025 |
— |
| 2025-01-01 |
ToolRL: Reward is All Tool Learning Needs |
NeurIPS 2025 |
— |
| 2025-01-01 |
Crucible: Quantifying the Potential of Control Algorithms through LLM Agents |
NeurIPS 2025 |
— |
| 2025-01-01 |
Effective Policy Learning for Multi-Agent Online Coordination Beyond Submodular Objectives |
NeurIPS 2025 |
— |
| 2025-01-01 |
WALL-E: World Alignment by NeuroSymbolic Learning improves World Model-based LLM Agents |
NeurIPS 2025 |
— |
| 2025-01-01 |
AutoData: A Multi-Agent System for Open Web Data Collection |
NeurIPS 2025 |
— |
| 2025-01-01 |
The Lighthouse of Language: Enhancing LLM Agents via Critique-Guided Improvement |
NeurIPS 2025 |
— |
| 2025-01-01 |
Learning and Planning Multi-Agent Tasks via an MoE-based World Model |
NeurIPS 2025 |
— |
| 2025-01-01 |
MLZero: A Multi-Agent System for End-to-end Machine Learning Automation |
NeurIPS 2025 |
— |
| 2025-01-01 |
Mean-Field Sampling for Cooperative Multi-Agent Reinforcement Learning |
NeurIPS 2025 |
— |
| 2025-01-01 |
CAML: Collaborative Auxiliary Modality Learning for Multi-Agent Systems |
NeurIPS 2025 |
— |
| 2025-01-01 |
Sample-Efficient Tabular Self-Play for Offline Robust Reinforcement Learning |
NeurIPS 2025 |
— |
| 2025-01-01 |
AgentAuditor: Human-level Safety and Security Evaluation for LLM Agents |
NeurIPS 2025 |
— |
| 2025-01-01 |
LLM-PySC2: Starcraft II learning environment for Large Language Models |
NeurIPS 2025 |
— |
| 2025-01-01 |
Robust Cross-modal Alignment Learning for Cross-Scene Spatial Reasoning and Grounding |
NeurIPS 2025 |
— |
| 2025-01-01 |
OWMM-Agent: Open World Mobile Manipulation With Multi-modal Agentic Data Synthesis |
NeurIPS 2025 |
— |
| 2025-01-01 |
MOSDT: Self-Distillation-Based Decision Transformer for Multi-Agent Offline Safe Reinforcement Learning |
NeurIPS 2025 |
— |
| 2025-01-01 |
Multi-scale Temporal Prediction via Incremental Generation and Multi-agent Collaboration |
NeurIPS 2025 |
— |
| 2025-01-01 |
MAT-Agent: Adaptive Multi-Agent Training Optimization |
NeurIPS 2025 |
— |
| 2025-01-01 |
Agentic RL Scaling Law: Spontaneous Code Execution for Mathematical Problem Solving |
NeurIPS 2025 |
— |
| 2025-01-01 |
From Self-Check to Consensus: Bayesian Strategic Decoding in Large Language Models |
NeurIPS 2025 |
— |
| 2025-01-01 |
A Near-optimal, Scalable and Parallelizable Framework for Stochastic Bandits Robust to Adversarial Corruptions and Beyond |
NeurIPS 2025 |
— |
| 2025-01-01 |
Graphs Help Graphs: Multi-Agent Graph Socialized Learning |
NeurIPS 2025 |
— |
| 2025-01-01 |
Thought Communication in Multiagent Collaboration |
NeurIPS 2025 |
— |
| 2025-01-01 |
PANDA: Towards Generalist Video Anomaly Detection via Agentic AI Engineer |
NeurIPS 2025 |
— |
| 2025-01-01 |
MaintainCoder: Maintainable Code Generation Under Dynamic Requirements |
NeurIPS 2025 |
— |
| 2025-01-01 |
RobotSmith: Generative Robotic Tool Design for Acquisition of Complex Manipulation Skills |
NeurIPS 2025 |
— |
| 2025-01-01 |
In-Context Fully Decentralized Cooperative Multi-Agent Reinforcement Learning |
NeurIPS 2025 |
— |
| 2025-01-01 |
Hierarchical Semantic-Augmented Navigation: Optimal Transport and Graph-Driven Reasoning for Vision-Language Navigation |
NeurIPS 2025 |
— |
| 2025-01-01 |
OpenHype: Hyperbolic Embeddings for Hierarchical Open-Vocabulary Radiance Fields |
NeurIPS 2025 |
— |
| 2025-01-01 |
CREA: A Collaborative Multi-Agent Framework for Creative Image Editing and Generation |
NeurIPS 2025 |
— |
| 2025-01-01 |
CAM: A Constructivist View of Agentic Memory for LLM-Based Reading Comprehension |
NeurIPS 2025 |
— |
| 2025-01-01 |
Multi-Agent Collaboration via Evolving Orchestration |
NeurIPS 2025 |
— |
| 2025-01-01 |
G-Memory: Tracing Hierarchical Memory for Multi-Agent Systems |
NeurIPS 2025 |
— |
| 2025-01-01 |
Compiler-R1: Towards Agentic Compiler Auto-tuning with Reinforcement Learning |
NeurIPS 2025 |
— |
| 2025-01-01 |
Code Graph Model (CGM): A Graph-Integrated Large Language Model for Repository-Level Software Engineering Tasks |
NeurIPS 2025 |
— |
| 2025-01-01 |
KVCOMM: Online Cross-context KV-cache Communication for Efficient LLM-based Multi-agent Systems |
NeurIPS 2025 |
— |
| 2025-01-01 |
3D-Agent: A Tri-Modal Multi-Agent Responsive Framework for Comprehensive 3D Object Annotation |
NeurIPS 2025 |
— |
| 2025-01-01 |
AgentNet: Decentralized Evolutionary Coordination for LLM-based Multi-Agent Systems |
NeurIPS 2025 |
— |
| 2025-01-01 |
TwinMarket: A Scalable Behavioral and Social Simulation for Financial Markets |
NeurIPS 2025 |
— |
| 2025-01-01 |
Multi-agent Markov Entanglement |
NeurIPS 2025 |
— |
| 2025-01-01 |
Many Minds, One Goal: Time Series Forecasting via Sub-task Specialization and Inter-agent Cooperation |
NeurIPS 2025 |
— |
| 2025-01-01 |
Group-in-Group Policy Optimization for LLM Agent Training |
NeurIPS 2025 |
— |
| 2025-01-01 |
Debate or Vote: Which Yields Better Decisions in Multi-Agent Large Language Models? |
NeurIPS 2025 |
— |
| 2025-01-01 |
GAM-Agent: Game-Theoretic and Uncertainty-Aware Collaboration for Complex Visual Reasoning |
NeurIPS 2025 |
— |
| 2025-01-01 |
GraphMaster: Automated Graph Synthesis via LLM Agents in Data-Limited Environments |
NeurIPS 2025 |
— |
| 2025-01-01 |
Video Action Differencing |
ICLR 2025 |
— |
| 2025-01-01 |
ComaDICE: Offline Cooperative Multi-Agent Reinforcement Learning with Stationary Distribution Shift Regularization |
ICLR 2025 |
— |
| 2025-01-01 |
Monte Carlo Planning with Large Language Model for Text-Based Game Agents |
ICLR 2025 |
— |