On-device research index

arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

169,051 papers · 148 categories

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8 results for “meta-agent”

Controllable Financial Market Generation with Diffusion Guided Meta Agentcs.CE

Paper proposes DigMA to generate controllable financial market orders.

problem Generating realistic financial market orders with controllability.

method DigMA model using conditional diffusion and meta agent.

result DigMA achieves superior controllability and generation fidelity.

financial markets order generation controllability meta agent conditional diffusion

2024-08-23abs ↗pdf ↗

Learning to Coordinate Multiple Reinforcement Learning Agents for Diverse Query Reformulationcs.LG

A method for efficient reinforcement learning query reformulation.

problem Efficiently learn diverse strategies for query reformulation.

method A framework with specialized sub-agents and a meta-agent trained on full data.

result Improved generalization performance and diversity of reformulation strategies.

reinforcement learning query reformulation diversity meta-agent reinforcement learning agents

2018-09-27abs ↗pdf ↗

Offline Meta Learning of Explorationcs.LG

Meta-agent learns effective exploration from offline data.

problem Design a meta-agent to quickly maximize reward in unseen tasks.

method Bayesian RL approach with adaptive neural belief estimate.

result Meta-agent learns effective exploration behavior from diverse tasks.

Offline Meta Reinforcement Learning Bayesian Reinforcement Learning Exploration Strategy Meta-Agent MDP Ambiguity

2020-08-06abs ↗pdf ↗

The Self Driving Portfolio: Agentic Architecture for Institutional Asset Managementcs.AI

AI agents manage portfolios, improving on human oversight.

problem Improving strategic asset allocation for institutional investors.

method 50 specialized agents produce capital market assumptions, construct portfolios, critique, and vote on each other's output.

result Meta-agent compares forecasts with realized returns and improves agent performance.

AI portfolio management asset allocation agentic architecture institutional investing

2026-04-02abs ↗pdf ↗

Multi-Agent Meta-Reinforcement Learning for Self-Powered and Sustainable Edge Computing Systemscs.LG

Paper proposes MAMRL for efficient energy dispatch in self-powered edge computing systems.

problem High energy consumption in self-powered edge computing systems.

method Developed a semi-distributed data-driven MAMRL framework to solve a two-stage linear stochastic programming problem.

result The proposed MAMRL framework reduces up to 11% non-renewable energy usage and 22.4% energy cost.

edge computing meta-reinforcement learning energy dispatch self-powered wireless networks

2020-02-20abs ↗pdf ↗

Prosocial or Selfish? Agents with different behaviors for Contract Negotiation using Reinforcement Learningcs.LG

Deep learning agents negotiate contracts with prosocial or selfish behaviors.

problem Training agents to negotiate contracts with varying behaviors.

method Multi-Agent Reinforcement Learning, modeling prosocial and selfish behaviors, training a meta agent.

result Trained agents hold their own against human players and emulate human behavior.

Reinforcement Learning Contract Negotiation Multi-Agent Systems Prosocial Behavior Selfish Behavior

2018-09-19abs ↗pdf ↗

HARLF: Hierarchical Reinforcement Learning and Lightweight LLM-Driven Sentiment Integration for Financial Portfolio Optimizationq-fin.PM

A novel framework combines LLMs and RL for financial portfolio optimization.

problem Optimizing financial portfolios using sentiment analysis and market indicators.

method Hierarchical RL structure with base, meta, and super-agents.

result Achieved a 26% annualized return and Sharpe ratio of 1.2.

portfolio optimization sentiment analysis reinforcement learning financial markets large language models

2025-07-24abs ↗pdf ↗

FinMarBa: A Market-Informed Dataset for Financial Sentiment Classificationcs.CL

Paper presents a hybrid framework combining sentiment analysis and market indicators for financial portfolio optimization.

problem Improving financial portfolio optimization through better integration of sentiment and market data.

method A three-tier hierarchical RL framework integrating LLMs, DRL, and market data.

result Achieved a 26% annualized return and Sharpe ratio of 1.2, outperforming benchmarks.

portfolio optimization sentiment analysis reinforcement learning financial markets large language models

2025-07-24abs ↗pdf ↗