LiveMACE: Process-Aware Evaluation of LLM Agent Capabilities in Evolving Markets
cs.AI, cs.CL
Submitted: 2026-10-07
Updated: 2026-10-07
Code: https://github.com/RaymondVoldemortFu/LiveMACE
Sources
- AgentBench: Evaluating LLMs as Agents
- WebArena: A Realistic Web Environment for Building Autonomous Agents
- SWE-bench: Can Language Models Resolve Real-World GitHub Issues?
- Gaia2: Benchmarking LLM Agents on Dynamic and Asynchronous Environments
- AI-Trader: Benchmarking Autonomous Agents in Real-Time Financial Markets
- ReAct: Synergizing Reasoning and Acting in Language Models
- DeepSeek-V3.2: Pushing the Frontier of Open Large Language Models
- TheAgentCompany: Benchmarking LLM Agents on Consequential Real World Tasks
- Odysseys: Benchmarking Web Agents on Realistic Long Horizon Tasks
- WildClawBench: A Benchmark for Real-World, Long-Horizon Agent Evaluation
- SWE-Marathon: Can Agents Autonomously Complete Ultra-Long-Horizon Software Work?
- FinanceBench: A New Benchmark for Financial Question Answering
- PIXIU: A Large Language Model, Instruction Data and Evaluation Benchmark for Finance
- FinBen: A Holistic Financial Benchmark for Large Language Models
- FinMem: A Performance-Enhanced LLM Trading Agent with Layered Memory and Character Design
- A Multimodal Foundation Agent for Financial Trading: Tool-Augmented, Diversified, and Generalist
- TradingAgents: Multi-Agents LLM Financial Trading Framework
- INVESTORBENCH: A Benchmark for Financial Decision-Making Tasks with LLM-based Agent
- From Knowing to Doing: A Memory-Controlled Benchmark for LLM Trading Agents on Stock Markets
- FinEvolveBench: A Benchmark for Self-Evolving Agents on Low-Repetition Tasks with Implicit Rewards
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