AI 论文精选速递
2026年11月09日 · 追踪前沿研究
TradingAgents: Multi-Agents LLM Financial Trading Framework
Yijia Xiao, Edward Sun 等4人
A multi-agent framework using large language models for stock trading simulates real-world trading firms, improving performance metrics like cumulative returns and Sharpe ratio.
https://arxiv.org/abs/2412.20138
https://hjfy.top/arxiv/2412.20138
https://github.com/tauricresearch/tradingagents (121326)
TokenEconomizer: Experience-Driven Black-Box Cost Control for Coding Agents
Aaron J. Li, Weijia Xu 等11人
TokenEconomizer reduces recurring token costs of coding agents across sequential real-world tasks by pruning irrelevant tools, injecting micro-skills, and interrupting failure loops.
https://arxiv.org/abs/2610.22732
https://hjfy.top/arxiv/2610.22732
https://github.com/microsoft/TokenEconomizer (5065)
Persistent Recursive Worlds Enable Autonomous Software Evolution
Beichen Huang, Zhenyu Liang 等4人
Genesis organizes long-horizon software development around a persistent project rather than persistent agents, enabling multi-day compiler construction and numerical module reimplementation with low cost and high performance.
https://arxiv.org/abs/2608.10450
https://hjfy.top/arxiv/2608.10450
https://github.com/EMI-Group/genesis (663)
Unlimited OCR Works
Youyang Yin, Huanhuan Liu 等17人
Unlimited OCR introduces Reference Sliding Window Attention to eliminate growing memory consumption during long-sequence OCR tasks, enabling efficient transcription of multiple pages in a single forward pass.
https://arxiv.org/abs/2606.23050
https://hjfy.top/arxiv/2606.23050
https://github.com/baidu/Unlimited-OCR (30894)
OpenDevin: An Open Platform for AI Software Developers as GeneralistAgents
Xingyao Wang, Boxuan Li 等24人
OpenDevin is a platform for developing AI agents that interact with the world by writing code, using command lines, and browsing the web, with support for multiple agents and evaluation benchmarks.
https://arxiv.org/abs/2407.16741
https://hjfy.top/arxiv/2407.16741
https://github.com/opendevin/opendevin (92969)
HairDeck: Animation-Ready Stylized Hair Cards from a Single Image
Yuze He, Yixiang Wei 等6人
HairDeck generates stylized hair cards and spring-bone animations as unordered token sets using a diffusion transformer, improving accuracy and speed over prior methods.
https://arxiv.org/abs/2610.40599
https://hjfy.top/arxiv/2610.40599
https://github.com/hyz317/HairDeck (951)
Mem0: Building Production-Ready AI Agents with Scalable Long-Term Memory
Prateek Chhikara, Dev Khant 等5人
Mem0, a memory-centric architecture with graph-based memory, enhances long-term conversational coherence in LLMs by efficiently extracting, consolidating, and retrieving information, outperforming existing memory systems in terms of accuracy and computational efficiency.
https://arxiv.org/abs/2504.19413
https://hjfy.top/arxiv/2504.19413
https://github.com/mem0ai/mem0 (68626)
VisSearch-Bench: Evaluating Long Horizon Visual Search in Multimodal Agents
ZhengXian Wu, Qianhao Nie 等13人
VisSearch-Bench evaluates multimodal agents on visually intensive search tasks that require integrating visual context with external information, showing that even the best system fully solves only 26.47% of tasks.
https://arxiv.org/abs/2611.04894
https://hjfy.top/arxiv/2611.04894
https://github.com/antins-labs/VisSearch-Bench-v1 (61)
MinerU2.5: A Decoupled Vision-Language Model for EfficientHigh-Resolution Document Parsing
Junbo Niu, Zheng Liu 等61人
MinerU2.5, a 1.2B-parameter document parsing vision-language model, achieves state-of-the-art recognition accuracy with computational efficiency through a coarse-to-fine parsing strategy.
https://arxiv.org/abs/2509.22186
https://hjfy.top/arxiv/2509.22186
https://github.com/opendatalab/MinerU (83316)
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生成时间: 2026-11-09 08:30
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