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The Aspirations Of HPE And Dell In The Quantum-Classical HPC Datacenter
Hewlett Packard Enterprise and Dell are outlining their strategic goals for integrating quantum and classical high-performance computing within modern datacenters.
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Valfortec plans €300m data center campus in Alicante, Spain
Valfortec is planning to develop a 60MW data center campus in Alicante, Spain, with an investment of 300 million euros.
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长飞光纤等在武汉成立智能创投基金，出资额5亿
Yangtze Optical Fibre and Cable has partnered with other entities to establish a 500 million yuan venture capital fund in Wuhan focused on smart technologies.
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How Smartsheet built a remote MCP server on AWS
Smartsheet has detailed the architecture and AWS-based infrastructure used to deploy a remote Model Context Protocol server.
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Reason Less, Verify More: Deterministic Gates Recover a Silent Policy-Violation Failure Mode in Tool-Using LLM Agents
Researchers identify a failure mode where LLM agents successfully complete tasks while violating safety policies, and propose deterministic gates as a mitigation strategy.
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SPQR: A Multi-Dimensional Benchmark for Safety Alignment under Benign Model Adaptation
A new benchmark, SPQR, evaluates the stability of safety alignment in text-to-image models when subjected to common downstream fine-tuning techniques.
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To Answer or to Abstain: Mitigating Search-Agent Hallucinations via Abstention-Aware Reinforcement Learning
Researchers have developed an abstention-aware reinforcement learning approach to reduce hallucinations in search-augmented LLMs by penalizing incorrect answers when retrieval fails.
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Agent Hacks Agent: Autoresearch for Production-Agent Red-Teaming
Researchers propose a new red-teaming framework that uses autonomous agents to identify security vulnerabilities in production LLM agent workflows.
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ReflectWorld-MM: An Entity-Oriented Multi-Media Memory System for Open-Ended Video Streams
Researchers developed ReflectWorld-MM, a multimedia memory system that organizes long-term video stream data around persistent entities rather than individual frames.
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GrandCode: Achieving Grandmaster Level in Competitive Programming via Agentic Reinforcement Learning
GrandCode is a new multi-agent reinforcement learning system that aims to achieve competitive programming performance at the level of human grandmasters.
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Gefen: Optimized Stochastic Optimizer
The proposed Gefen optimizer reduces the memory footprint of large-scale model training by sharing second-moment estimates and quantizing first-moment states.
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The Ebb and Flow of Multimodal Focus: Scheduling Visual Relay Windows for Grounded VLM Reasoning
This study analyzes the internal attention dynamics of vision-language models to explain why visual grounding degrades and proposes scheduling visual relay windows to stabilize reasoning.
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ActiveFly-Bench: Aligning Embodied Question Answering with Vision-Language-Action for Aerial Embodied Perception
ActiveFly-Bench is a new benchmark designed to evaluate aerial embodied perception by linking high-level task understanding, behavior planning, and low-level control for unmanned aerial vehicles.
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Embodied-R1.5: Evolving Physical Intelligence via Embodied Foundation Models
Embodied-R1.5 is a new foundation model designed to unify embodied reasoning and physical intelligence using a large-scale dataset of 15 billion tokens.
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Valid $\ne$ Necessary: Diagnosing Latent Inefficiency in Chain-of-Thought
The study identifies a critical inefficiency in Chain-of-Thought prompting where models generate redundant but logically valid reasoning steps that current evaluators fail to penalize.
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Remembering Distinct Items, Not Tokens: A Learnable Dirichlet-Process Cache Between State-Space Models and Attention
This paper proposes a learnable Dirichlet-process cache that stores only novel inputs to bridge the gap between state-space models and attention mechanisms.
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The Path to Self-Evolving Clinical Systems: Scaling Medical Agents from Assistance to Autonomy
This paper outlines a deployment-focused pathway for transitioning medical AI agents from simple assistants to autonomous clinical systems.
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IdeaTrail: Full-Process Agent Trajectories for Scientific Ideation
IdeaTrail is a new dataset designed to capture the complete, multi-stage workflow of AI agents performing scientific ideation and research tasks.
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Are LLMs Ready for Scientific Discovery? A Capability-Oriented Benchmark for AI Scientists
Researchers have introduced SDABench, a new benchmark designed to evaluate the scientific data analysis capabilities of large language models across six distinct areas.
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SWE-MERA: A Dynamic Benchmark for Agenticly Evaluating Large Language Models on Software Engineering Tasks
The authors introduce SWE-MERA, a dynamic benchmark designed to mitigate data contamination and improve the evaluation of LLMs on software engineering tasks.
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Knowledge Graphs Meet Graph Neural Networks: A Comprehensive Survey
This paper provides a comprehensive survey and a new two-level taxonomy of Graph Neural Network methodologies applied across knowledge graph technologies.
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MemDecay: Region-Aware KV Cache Eviction for Efficient LLM Agent Inference
MemDecay is a new memory management technique that optimizes LLM agent inference by using region-aware KV cache eviction based on semantic structure.
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Model Collapse: On Recursion, Noise, and Uncharted Machine Visions
This paper examines the phenomenon of model collapse from both engineering and creative perspectives, exploring how recursive training on AI-generated data affects model output.
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Unlocking Parallelism in Autoregressive Language Models via Speculative Decoding with Progressive Tree Drafting
Researchers propose a new speculative decoding method that improves large language model inference speed by utilizing progressive tree drafting to better exploit parallel processing.