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深成指、创业板指午后跌超3%
Major Chinese stock indexes fell sharply in afternoon trading, with computing hardware and semiconductor chip sectors leading the decline.
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MCP tool design: Practical approaches and tradeoffs
Amazon Web Services has published a guide detailing practical context engineering approaches to optimize Model Context Protocol tool design.
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Tencent launches Hunyuan Hy3, integrates model across multiple products
Tencent has released Hunyuan Hy3, a Mixture of Experts reasoning model featuring 295 billion parameters and a 256K context window, which has been integrated across several of its products.
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腾势N8公告亮相，定位大五座纯电豪华SUV
BYD's premium brand Denza has officially unveiled the Denza N8, a luxury electric SUV featuring its second-generation blade battery and fast-charging technology.
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From Hugging Face to Amazon SageMaker Studio in one click
Hugging Face has launched a one-click integration with Amazon SageMaker Studio to streamline the deployment and training of machine learning models.
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Beware What You Autocomplete: Forensic Attribution of Backdoored Code Completions
Researchers have developed CodeTracer, a forensic framework designed to detect and trace malicious backdoor attacks in large language model code completion systems.
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3100 Opinions on Code Review in an AI World: Building Causal Theory from Practitioner Discourse
This study analyzes practitioner perspectives to build a causal theory regarding how AI coding agents affect the process and outcomes of code reviews.
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Shift & Drift: A Zero-Shot Benchmark for Generalizable and Robust Autonomous Driving Motion Planning
Researchers have introduced Shift & Drift, a new benchmark designed to evaluate the robustness and generalization of autonomous driving motion planners under distribution shifts.
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Training and Evaluating Diffusion Policies with Long Context Lengths
The study benchmarks the performance of robotic diffusion policies as their observation context length is increased, addressing memory limitations in dexterous manipulation.
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Using AI-based Learning Assistants in Higher Education: A Large-Scale Descriptive Analysis
A large-scale study analyzes the usage patterns of an AI-based learning assistant among over 77,000 higher education students in distance learning programs.
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Blind-Spots-Bench: Evaluating Blind Spots in Multimodal Models
A new evaluation suite called Blind-Spots-Bench has been developed to identify simple tasks that humans easily perform but multimodal AI models struggle to complete.
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AutoPersonas: A Multi-Timescale Loop Engine for Open-Ended Persona Evolution
The AutoPersonas framework addresses the issue of behavioral collapse in long-term persona agents by enabling open-ended evolution across multiple timescales.
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Diffusion-GR2: Diffusion Generative Reasoning Re-ranker
The authors present Diffusion-GR2, a generative reasoning re-ranker that utilizes block-diffusion language models to accelerate inference speeds in recommendation systems.
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Autonomous heterogeneous catalyst discovery with a self-evolving multi-agent digital twin
Researchers developed CatDT, a self-evolving multi-agent digital twin system designed to autonomously simulate and discover heterogeneous catalysts.
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MasFACT: Continual Multi-Agent Topology Learning via Geometry-Aware Posterior Transfer
MasFACT is a continual learning framework designed to optimize and adapt communication topologies among multi-agent systems across evolving tasks.
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Concretized Proposition Prompting Resolves Composition-Knowledge Dichotomy in Large Language Models
A prompting framework called Concretized Proposition Prompting has been developed to improve reasoning and knowledge retrieval in large language models, particularly for medical tasks.
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Human-like Object Grouping in Self-supervised Vision Transformers
A new behavioral benchmark evaluates how closely the emergent object segmentation properties of self-supervised vision transformers align with human visual perception.
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An Online Reference-Free Evaluation Framework for Flowchart Image-to-Code Generation
This paper introduces an online, reference-free evaluation framework to monitor the quality of flowchart image-to-code generation by vision-language models during inference.
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MultiFair: Multimodal Balanced Fairness-Aware Medical Classification with Dual-Level Gradient Modulation
The MultiFair framework addresses modality bias and demographic unfairness in multimodal medical classification models using dual-level gradient modulation.
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InvestPhilBench: A Multi-Layer Benchmark for Evaluating Large Language Model Procedural Reasoning in Expert Investment Philosophy
Researchers have introduced InvestPhilBench, a multi-layer benchmark designed to evaluate how well large language models can reconstruct and apply expert investment decision frameworks.
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Track2Map: Online Deformable SLAM with Motion-Aware Pose Optimization in Robotic Surgery
Track2Map is a new real-time 3D Gaussian Splatting system designed to reconstruct deformable anatomy during robotic surgery without relying on precise camera trajectory priors.
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LEEVLA: Seeing What Matters in Latent Environment Evolution for Vision-Language-Action
The proposed LEEVLA architecture improves vision-language-action models for robotics by focusing on critical environmental changes rather than treating all visual data equally.
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Towards Efficient Large Language Model Serving: A Survey on System-Aware KV Cache Optimization
This survey paper categorizes and reviews recent system-level optimizations for key-value caches to improve the efficiency and throughput of large language model serving.
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Can We Trust LLM's Logic? Quantifying Uncertainty, Coherence, and Robustness via a Graph-Based Framework
A new graph-based framework evaluates the logical consistency and uncertainty of large language model reasoning steps rather than just checking the final output.