AI & Machine Learning · Computer Science & AI
Multiagent Systems
The newest papers in Multiagent Systems that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
829 papers, from 4 September 2026 to 5 November 2026: 829 arXiv preprints.
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Multi-agent Scaling Across Disjunctive and Compensatory Tasks
Multi-agent LLM systems are often expected to improve as team size increases, yet the scaling behavior may depend on task structure.AgentWorld: Benchmarking Long-Horizon Collaboration of Multi-agent LLMs
Existing multi-agent benchmarks primarily test in competitive settings, short-horizon interactions under 20 steps, or simply aggregate individual performance, failing to isolate and highlight…Deep Reinforcement Learning for Equity Trading: Benchmarking Actor-Critic Methods with Forward Retraining
Consistently profitable trading is difficult because equity markets are noisy, non-stationary, and only partially predictable from historical data.Choir: An Open Protocol for Distributed Multi-Agent Autoformalization
AI agents can now formalize entire textbooks and major theorems in proof assistants such as Lean, but current efforts are typically centralized: a single team runs all agents and bears the full…Overview of the TREC 2025 Million Large Language Models track
Agentic AI envisions ecosystems of intelligent agents collaboratively solving complex tasks with minimal human intervention.Communication between Frozen Large Language Models via Prompt Optimization in a Referential Game
We study communication between two frozen large language models from different providers, with different tokenizers, accessed through their API endpoints.Decentralized Master-Mind: Joint Action Refinement through Iterative Intent Denoising in Multi-Agent Pathfinding
Decentralized multi-agent path finding (MAPF) with communication requires agents to reach individual goals without collisions under partial observability.EngramRAG: Dynamic Usage-Weighted Topology and Synaptic Consolidation for Multi-Hop Agentic Memory
As autonomous LLM agents are deployed across multi-session environments, conventional memory architectures suffer from Associative Blindness (inability to traverse multi-hop relational…On Evaluating and Improving Conversational Agents in Production
We present a framework for evaluating and improving a large-scale, multi-agent shopping assistant in production, and report lessons from its use.Codetta: High-Capacity, Keyless, and Undetectable Multi-Agent Collusion
Multi-agent systems built on large language models (LLMs) are increasingly deployed in high-stakes settings such as finance, healthcare, and software engineering, where agents coordinate through…AlphaDiverse: Post-Training Local Quantitative Research Agents for Diverse Exploration in Alpha Factor Mining
Large language model (LLM)-based multi-agent systems can automate alpha factor mining, but their reliance on external APIs limits control over cost, availability, and confidentiality.AI-Moderated Interviews for Market Research and Digital Twins Calibration
AI-moderated interviews are emerging as a scalable market-research method for generating consumer insights and building consumer "digital twins.Temperament Engineering: Designing Strategic Behavioural Diversity in Robot Swarms
No two robots are truly identical: calibration, battery state, sensor drift and wear give every swarm a distribution of behaviour rather than a single point, usually treated as an imperfection to be…REAT: A Reflective Experience-Augmented Tutoring Framework for Multi-turn Mathematical Instruction
Current Large Language Models (LLMs) excel at solving complex mathematical problems, yet this proficiency does not inherently translate into effective tutoring.Costly Voting in the Hotelling-Downs Model
We study a partial-participation variation of the Hotelling-Downs model.Who Holds the Pen? Let Specifications, Not Agents, Sign Off
Large language model agents increasingly combine generation, decision-making, execution, and self-evaluation within a single agentic loop.Pairwise Approximation Can Select the Wrong Multi-Robot Plan
Multi-robot coordination methods often score a joint plan from singleton and pairwise terms, leaving out the terms that involve three or more robots.Augur: A Synthetic Decision Lab for Rehearsing Reactions to Product and Policy Changes
Before a product or policy change ships, the question that matters is how people will react to it.Multi-Dimensional Matching
We study a matching mechanism where agents and objects are described by features rather than complete rankings.GRASP: Generating, Revising, and Assessing for Strategic Planning with Agentic AI
Large Language Models (LLMs) typically exhibit a performance profile where reliability degrades as task complexity increases.