Daily edition · AI Research
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583 articles · 7 sources · 579 papers ·
Top topics: AI Research · AI · Information Retrieval
Why the default 50/50 split is the wrong move when your treatment is more expensive than your control, and how cost-based sampling weights fix it The post Optimal Traffic Allocation Under Heterogeneous Variant Cost…
Three conditions that must hold before splitting prefill from decode pays off, and why chunked prefill is the right default below that threshold. The post Disaggregation Is a Thousand-GPU Problem appeared first on…
Power BI Premium is gone. Microsoft Fabric took its place. Here's what actually changed for you, what didn't, and where to start — without the panic. The post The Power BI Developer's Survival Guide to Microsoft Fabric…
Learn how to run a lot of parallel coding agents without expensive, powerful hardware at home The post How to Run 10+ Claude Code Sessions Without a Powerful Computer appeared first on Towards Data Science.
OpenAI launched GPT-6 Astra with huge gains in computer use, science, and cybersecurity; IFM released six fully open K2 Horizon models; Google mapped the complete male fruit-fly brain; xAI shipped Grok Bot for…
GPT-6 Astra can operate computers, build software, solve research problems, and hunt zero-day vulnerabilities. The bigger change is that OpenAI increasingly expects you to give AI work instead of prompts.
arXiv:2608.28974v2 Announce Type: replace Abstract: Clinically relevant oncology information is distributed across heterogeneous, longitudinal documentation, creating substantial abstraction burden and requiring…
arXiv:2609.02364v2 Announce Type: replace-cross Abstract: Existing Human-Robot Interaction (HRI) literature has focused on identifying and structuring errors, failures, conflicts, and knowledge issues (called in this…
arXiv:2609.03756v1 Announce Type: cross Abstract: We present ENEAS, a unified, text-promptable method for instance tracking and semantic discovery. Text-promptable segmentation models, including the latest foundation…
arXiv:2609.03920v1 Announce Type: new Abstract: The emergence of agentic AI and LLM-based multi-agent systems (MAS) presents unprecedented opportunities for automating complex tasks, while simultaneously raising…
arXiv:2602.10009v3 Announce Type: replace Abstract: Large Language Models (LLMs) are unable to reliably reason about specific physical systems. Attempts to imbue LLMs with knowledge of the necessary physics concepts…
arXiv:2609.04075v1 Announce Type: cross Abstract: AI agents have recently demonstrated strong performance in automated vulnerability patching. However, existing evaluations often validate a patch only by testing whether…
arXiv:2604.05460v2 Announce Type: replace-cross Abstract: Large language model (LLM) evaluation platforms increasingly rely on pairwise human judgments. These data are noisy, sparse, and non-uniform, yet leaderboards…
arXiv:2609.04167v1 Announce Type: cross Abstract: Repository-level software engineering benchmarks have significantly advanced the evaluation of coding agents, but existing benchmarks primarily measure whether generated…
arXiv:2609.03611v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) are increasingly used to evaluate robot manipulation outcomes, but existing benchmarks offer limited evidence of cross-domain…
arXiv:2310.20096v2 Announce Type: replace-cross Abstract: The data market design problem is a problem in economic theory to find a set of signaling schemes (statistical experiments) to maximize expected revenue to the…
arXiv:2609.04030v1 Announce Type: new Abstract: IRWOZ has improved industrial human-robot interaction (HRI) dialogue systems through domain-specific annotations. However, its initial version contains substantial noise…
arXiv:2609.03494v1 Announce Type: new Abstract: Long-output reasoning has made the key--value (KV) cache a critical memory bottleneck for efficient LLM serving. Existing KV compression methods usually rely on a…
arXiv:2609.03892v1 Announce Type: cross Abstract: 3D spatial reasoning underpins understanding and acting in the physical world, yet it remains unreliable in current multimodal large language models (MLLMs). These…
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