AI 论文精选速递
2026年10月27日 · 追踪前沿研究
Harness^2: Recursive Agent Harnessing for an Open World
Ruiyao Xu, Yanfei Chen 等9人
Harness² improves agent execution harnesses through recursive task-level refinement and continual harness-level learning, boosting performance across benchmarks without ground-truth verifiers.
https://arxiv.org/abs/2610.14224
https://hjfy.top/arxiv/2610.14224
https://github.com/google-research/harness2 (19988)
Kronos: A Foundation Model for the Language of Financial Markets
Yu Shi, Zongliang Fu 等7人
Kronos, a specialized pre-training framework for financial K-line data, outperforms existing models in forecasting and synthetic data generation through a unique tokenizer and autoregressive pre-training on a large dataset.
https://arxiv.org/abs/2508.02739
https://hjfy.top/arxiv/2508.02739
https://github.com/shiyu-coder/Kronos (43861)
nanoMuse: An Open-Source Personal Agent for Every Device You Own
Guangyi Liu, Yong Liu 等3人
https://arxiv.org/abs/2610.08699
https://hjfy.top/arxiv/2610.08699
https://github.com/nano-muse/nanoMuse (2639)
Efficient Memory Management for Large Language Model Serving withPagedAttention
Woosuk Kwon, Zhuohan Li 等9人
PagedAttention algorithm and vLLM system enhance the throughput of large language models by efficiently managing memory and reducing waste in the key-value cache.
https://arxiv.org/abs/2309.06180
https://hjfy.top/arxiv/2309.06180
https://github.com/vllm-project/vllm (86094)
Internal Safety Collapse in Frontier Large Language Models
Yutao Wu, Xiao Liu 等10人
Frontier large language models exhibit Internal Safety Collapse, where they generate harmful content under specific task conditions, revealing inherent vulnerabilities despite alignment efforts.
https://arxiv.org/abs/2603.23509
https://hjfy.top/arxiv/2603.23509
https://github.com/wuyoscar/ISC-Bench (2343)
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 (82527)
PaddleOCR-VL-1.6: Expanding the Frontier of Document Parsing with Under-Optimized Region Refinement ...
Zelun Zhang, Hongen Liu 等15人
PaddleOCR-VL-1.6 enhances document parsing performance through targeted data optimization and progressive post-training techniques, achieving state-of-the-art results on OmniDocBench v1.6.
https://arxiv.org/abs/2606.03264
https://hjfy.top/arxiv/2606.03264
https://github.com/PaddlePaddle/PaddleOCR (91707)
Raven: The Harness of Harnesses for Composable Agentic Intelligence
EverMind AI
Raven is an open-source multi-agent ecosystem that autonomously builds and evolves modular harnesses, enabling cross-domain collaboration and expanding reliable task coverage through composable agent units.
https://arxiv.org/abs/2609.33439
https://hjfy.top/arxiv/2609.33439
https://github.com/EverMind-AI/Raven (5847)
COLLEAGUE.SKILL: Automated AI Skill Generation via Expert Knowledge Distillation
Tianyi Zhou, Dongrui Liu 等5人
Person-grounded AI skills are automatically distilled from heterogeneous traces into inspectable, correctable packages that capture both capabilities and behavioral patterns.
https://arxiv.org/abs/2605.31264
https://hjfy.top/arxiv/2605.31264
https://github.com/titanwings/colleague-skill (26054)
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生成时间: 2026-10-27 08:30
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