TradingAgents: Multi-Agents LLM Financial Trading Framework

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 (118199)

The Other Half of the Memory Wall: Serving 35B MoEs from SSD with Trained Routing Prediction

Edge0 enables efficient mixture-of-experts inference on consumer hardware by predicting expert routing ahead of time and using recovery adapters to maintain quality with minimal active memory.

https://arxiv.org/abs/2609.18063

https://hjfy.top/arxiv/2609.18063

https://github.com/Edge0-AI/edge0 (8683)

MOSS-Image Technical Report

MOSS-Image is an open diffusion transformer that combines high-fidelity synthesis with intent-aware prompt enhancement to generate text-rich, layout-coherent images, achieving state-of-the-art open-weight results on long-form text and layout benchmarks.

https://arxiv.org/abs/2610.23374

https://hjfy.top/arxiv/2610.23374

https://github.com/OpenMOSS/MOSS-Image (2215)

Hy-Nomas: Towards Free-form Interactive World Generation

Hy-Nomas is a video world model that uses causal attention and structured conditioning to generate interactive, multi-turn video segments with text and camera control.

https://arxiv.org/abs/2610.36729

https://hjfy.top/arxiv/2610.36729

https://github.com/Tencent-Hunyuan/Hy-Nomas (379)

TokenEconomizer: Experience-Driven Black-Box Cost Control for Coding Agents

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 (484)

Next-Concept Modeling: Fast, Parallel Coarse-to-Fine Text Generation

Next-Concept Modeling uses hierarchical discrete codes and parallel level-wise generation to accelerate diffusion language models while improving quality and reasoning performance.

https://arxiv.org/abs/2610.14162

https://hjfy.top/arxiv/2610.14162

https://github.com/HazyResearch/ncm (1258)

Building Auditable AI Text Detectors with Sparse Autoencoders

A pipeline using sparse autoencoders extracts interpretable linguistic features from neural detectors, yielding more accurate and explainable AI-generated text classification.

https://arxiv.org/abs/2610.30006

https://hjfy.top/arxiv/2610.30006

https://github.com/google-deepmind/detectorscope (249)

RSI-Anything: Unlocking Recursive Self-Improvement with World Models

RSI-Anything leverages predictive world models to guide action selection and adaptive learning, enabling recursive self-improvement across coding, interface navigation, laboratory planning, and scientific optimization tasks.

https://arxiv.org/abs/2610.13912

https://hjfy.top/arxiv/2610.13912

https://github.com/Gen-Verse/RSI-Anything (1056)

Geometric Context Transformer for Streaming 3D Reconstruction

LingBot-Map is a feed-forward 3D foundation model that reconstructs scenes from video streams using a geometric context transformer architecture with specialized attention mechanisms for coordinate grounding, dense geometric cues, and long-range drift correction, achieving stable real-time performan...

https://arxiv.org/abs/2604.14141

https://hjfy.top/arxiv/2604.14141

https://github.com/robbyant/lingbot-map (18465)