Kronos: A Foundation Model for the Language of Financial Markets

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 (46250)

FreeToken: Efficient Edge-Native MoE Serving with Bandwidth-Adaptive Execution

FreeToken is an edge-native Mixture-of-Experts serving system that dynamically maps computation and model state onto heterogeneous local hardware to run large open-weight models on personal machines.

https://arxiv.org/abs/2608.16157

https://hjfy.top/arxiv/2608.16157

https://github.com/FlashML-org/FreeToken (16437)

Harness^2: Recursive Agent Harnessing for an Open World

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 (22280)

Democratizing Robot-Use Agents: A Unified Harness with Open Models

Uni-robot-agent enables open-weight robot-use agents to surpass proprietary models in zero-shot manipulation and suggests joint development of four core capabilities for future training.

https://arxiv.org/abs/2611.01560

https://hjfy.top/arxiv/2611.01560

https://github.com/Open-RUA/uni-robot-agent (100)

Differentiable Data Augmentation with Kornia

This paper reviews the Kornia differentiable data augmentation module for both 2D and 3D tensors, integrating with PyTorch's autograd and optim, and benchmarks it against other frameworks.

https://arxiv.org/abs/2011.09832

https://hjfy.top/arxiv/2011.09832

https://github.com/arraiyopensource/kornia (12311)

Very Large-Scale Multi-Agent Simulation in AgentScope

Enhancements to the AgentScope platform improve scalability, efficiency, and ease of use for large-scale multi-agent simulations through distributed mechanisms, flexible environments, and user-friendly tools.

https://arxiv.org/abs/2407.17789

https://hjfy.top/arxiv/2407.17789

https://github.com/modelscope/agentscope (35312)

AgentScope 1.0: A Developer-Centric Framework for Building AgenticApplications

AgentScope enhances agentic applications by providing flexible tool-based interactions, unified interfaces, and advanced infrastructure based on the ReAct paradigm, supporting efficient and safe development and deployment.

https://arxiv.org/abs/2508.16279

https://hjfy.top/arxiv/2508.16279

https://github.com/agentscope-ai/agentscope (35312)

Efficient Memory Management for Large Language Model Serving withPagedAttention

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)

CUA-Master: Scaling Computer-use Agents through Open-World Recursive Improvements

CUA-Master uses nested recursive loops with open-world data and feedback-driven retries to continuously improve computer-use agents across diverse benchmarks.

https://arxiv.org/abs/2611.03126

https://hjfy.top/arxiv/2611.03126

https://github.com/xlyu0106/CUA-Master (86)