Knowledge catalogue
Juro Osawa / The Information: Anthropic says it is rolling back a covert Claude Code tracking feature to identify users based in China or affiliated with Chinese AI labs, after backlash — Anthropic is
@anthropicai: Anthropic says “some routine tasks like coding and debugging” on Fable 5 “will fall back to Opus 4.8” in “the near term” as it works to “reduce false positives” — Claude Fable 5 will be
arXiv:2606.31959v1 Announce Type: new Abstract: Depth-of-field control is a fundamental tool in photography, yet post-capture bokeh editing from a single image remains challenging. A practical editor
arXiv:2606.31077v1 Announce Type: new Abstract: Multi-modal image matching is essential for visual localization and multi-sensor fusion, but it is hindered by the scarcity of large-scale training data
Apparently we didn't talk enough about w̶o̶r̶k̶f̶l̶o̶w̶s̶ loops yet! See ya there! @steipete is now joining us for Crafting Software Factories! 📅 6pm Wed evening in SF after the @aiDotEngineer World's
arXiv:2603.17461v2 Announce Type: replace Abstract: Streaming autoregressive (AR) video generators combined with few-step distillation achieve low-latency, high-quality synthesis, yet remain difficult
ARC-AGI-3 is built different, it has dumbfounded almost all regular attempts so far because it's so much harder than anything that came before. It has no rules, it's agentic and has no explicit goals,
Are there any CS profs left at Berkeley and Stanford? Might as well just merge all the PhD students into the big labs at this point Department Chair of Electrical Engineering and Computer Sciences at
arXiv:2606.31711v1 Announce Type: new Abstract: Faithfulness -- how precisely a generated image aligns with its prompt -- is increasingly central to the real-world utility of text-to-image (T2I) model
Security researchers at Armadin Inc. today detailed an attack chain that runs arbitrary commands as root inside the sandbox behind Anthropic PBC’s Claude Cowork, escaping the isolation layer, with a s
arXiv:2503.05785v2 Announce Type: replace-cross Abstract: Generative Artificial Intelligence (AI) tools such as ChatGPT, Copilot, or Gemini have a crucial impact on academic research and teaching. Emp
As generative AI tools continue to evolve, we believe it's more important than ever to know what's AI-generated and what isn't. That’s why @GoogleDeepMind launched SynthID in 2023—a technology that ad
arXiv:2606.31422v1 Announce Type: new Abstract: Long-horizon language agents do not only choose actions; they carry a private model of the world from one decision to the next. When that model drifts,
arXiv:2606.30646v1 Announce Type: cross Abstract: Speech recruits the same executive, attentional, and working memory processes underlying instrumental activities of daily living, or IADLs, providing
arXiv:2606.31903v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) increasingly process long visual-token sequences, increasing the overall inference computation. Existing acce
arXiv:2606.31004v1 Announce Type: new Abstract: AI-generated video detection benchmarks such as GenVidBench and AIGVDBench are the de facto leaderboards, yet most evaluation protocols leave uncontroll
arXiv:2606.31556v1 Announce Type: new Abstract: Generating high-quality novel views at real-time frame rates remains a central challenge in 3D vision, particularly in sparse-view scenarios. Neural rad
arXiv:2606.32018v1 Announce Type: new Abstract: Classifiers based on Deep Neural Networks exhibit strong performance across domains, yet can fail catastrophically if they rely on spurious correlations
arXiv:2410.11894v3 Announce Type: replace-cross Abstract: Dynamical systems form the foundation of scientific discovery, traditionally modeled with predefined state variables such as the angle and ang
arXiv:2606.31614v1 Announce Type: cross Abstract: Engineering specifications such as interlocks, alarm rationalization tables, and cause-and-effect (C&E) matrices remain central to process control and
arXiv:2606.31772v1 Announce Type: new Abstract: Reliable individual re-identification (re-ID) of wildlife is essential for population monitoring, behavioral tracking, and conservation policy evaluatio
Autoresearch describes a feedback mechanism where AI agents can evaluate their own outputs and use that introspection to iteratively improve their reasoning and decision-making capabilities. This conc
arXiv:2606.31551v1 Announce Type: new Abstract: Training language models (LMs) remains a highly human-intensive process, even as frontier language model agents become increasingly capable at software
arXiv:2606.30811v1 Announce Type: new Abstract: Audio-video generation has recently gained unprecedented research attention, aiming to synthesize high-quality sounding video content with fine-grained
Amazon Web Services Inc. is reinventing the way data-intensive analytical workloads are handled by the Amazon OpenSearch Service with the launch of a new, purpose-built log analytics engine today. The
arXiv:2606.32007v1 Announce Type: new Abstract: We study agentic code generation in Dafny, where a model must generate both executable code and the proof artifacts for verification. We present AxDafny
Chris Metinko / Axios: B2B sales workspace startup Aligned raised a 60M Series B led by PeakSpan Capital, taking its total funding to 73.8M, and says it has 1,000+ customers — Aligned, a sales workspa
Release b9852 is a build version of llama.cpp, a C/C++ implementation that enables large language model inference with minimal setup and state-of-the-art performance across diverse hardware platforms
The search results show llama.cpp releases but do not contain specific information about release b9853. Based on the context from the llama.cpp project, b9853 is likely a development build release of
Based on the available search results, the specific release details for b9857 are not fully accessible, but this entry refers to a build release from the llama.cpp project. llama.cpp is a port of Face
Release b9858 is a continuous build-tagged release of llama.cpp , the open-source C/C++ project that enables large language model inference with minimal setup and optimized performance across diverse
Release b9859 of llama.cpp was released on July 1, 2026 , and includes updates to allow loading precompiled binary kernels from library in the OpenCL backend . This release continues development of th
arXiv:2606.30850v1 Announce Type: new Abstract: Large language models (LLMs) are typically deployed in multi-turn conversations, where each turn provides new evidence that should reduce epistemic unce
arXiv:2606.30923v1 Announce Type: cross Abstract: Imitation Learning is a natural framework for learning in sequential decision-making systems and has emerged as the dominant paradigm through which we
arXiv:2606.31861v1 Announce Type: cross Abstract: Dynamic epistemic logic represents belief change via model transformations induced by epistemic events. Its standard formulation (Baltag, Moss, Soleck
arXiv:2606.31308v1 Announce Type: new Abstract: This paper investigates the capability of Large Language Models (LLMs) to detect and classify floating-point errors statically in software code. We intr
This post humorously describes using Claude AI as a learning tool to understand Microsoft Teams functionality for first-time users, shared during an AI Engineer event discussion. The post suggests Cla
This post likely references a casual, positive experience at an event or space associated with @aiDotEngineer, highlighting a 'puppy zone' as a memorable or enjoyable feature. Without access to the fu
arXiv:2606.30700v1 Announce Type: cross Abstract: Self-supervised learning enables audio representations that transfer across domains and tasks. We present BEST-RQ-2, an evolution of BEST-RQ that reta
arXiv:2606.31892v1 Announce Type: cross Abstract: 'Any fool can know; the point is to understand.' A well-known remark often attributed to Einstein captures a widely shared intuition: understanding is
arXiv:2606.31338v1 Announce Type: cross Abstract: Recent music audio-language models achieve high accuracy on instrument question-answering benchmarks, but it remains unclear whether this reflects rob
arXiv:2606.31080v1 Announce Type: cross Abstract: Counterfactual explanation in abstract argumentation calls for an answer to the what-if query: would the topic argument still be accepted if the statu
arXiv:2606.30914v1 Announce Type: new Abstract: Event detection (ED) systems are typically evaluated on clean, curated text, leaving their robustness to real-world noise largely unexplored, particular
arXiv:2606.31002v1 Announce Type: new Abstract: Theorem-proving benchmarks evaluate proof search against fixed formal statements, but natural-language-to-Lean formalization must generate the formal st
Decision Execution Platforms represent an evolution beyond traditional dashboards by enabling organizations to not only visualize data insights but also automatically trigger and execute business deci
arXiv:2606.30863v1 Announce Type: new Abstract: Agents typically assume an expert user -- one with well-formed preferences about what they want -- and default to clarifying questions whenever the task
arXiv:2606.31169v1 Announce Type: new Abstract: Existing AI-assisted oracle bone inscription (OBI) visual recognition and understanding studies mainly focus on character-level, ignoring the long-form
As enterprise generative AI transitions from simple, conversational chatbots to autonomous multi-agent workflows, developers face a critical bottleneck: scale. In a production environment, an enterpri
arXiv:2606.31536v1 Announce Type: new Abstract: As Quantum Machine Learning (QML) transitions toward practical implementation, the field faces a critical architectural bottleneck that challenges the f
arXiv:2606.31134v1 Announce Type: new Abstract: While Large Language Models (LLMs) have demonstrated exceptional capabilities in mathematical reasoning, they frequently produce subtle errors that evad
arXiv:2606.31315v1 Announce Type: new Abstract: Speculative decoding accelerates inference by using a lightweight draft model to generate candidate tokens in parallel, and are then verified by the tar
arXiv:2606.22723v2 Announce Type: replace Abstract: Although Large Language Models (LLMs) excel in many tasks, their assessment in Portuguese has received less attention, particularly for open-ended,
arXiv:2606.31420v1 Announce Type: new Abstract: Test-Time Adaptation (TTA) enables models trained on a source domain to adapt online to unlabeled test data under distribution shifts. While recent TTA
arXiv:2606.31825v1 Announce Type: cross Abstract: Recent multimodal large language models have shown great promise in clinical image reasoning, but existing post-training pipelines remain predominantl
arXiv:2601.19506v4 Announce Type: replace Abstract: Blind face restoration remains a persistent challenge due to the inherent ill-posedness of reconstructing holistic structures from severely constrai
arXiv:2606.31844v1 Announce Type: cross Abstract: A local-to-global context mismatch arises when autoregressive traffic simulators trained on ego-centric driving logs are deployed in globally observab
arXiv:2606.30943v1 Announce Type: new Abstract: Russian and Arabic are among the major languages of scientific communication. Language barriers impede the exchange of research results between these co
arXiv:2606.31779v1 Announce Type: cross Abstract: Language models typically reason via explicit chain-of-thought (CoT), generating intermediate steps token-by-token. Latent CoT offers an alternative:
arXiv:2606.31326v1 Announce Type: new Abstract: Recently, unified image generation and understanding have been extensively explored. However, extending such unified modeling paradigms to the video dom
arXiv:2606.30919v1 Announce Type: cross Abstract: Edge-cloud inference collaborations are often designed with a routing estimator that decides whether to offload each frame from weak models at the edg