Knowledge catalogue
Harshita Mary Varghese / Reuters: Anthropic debuts Claude for Financial Advisors, with connectors to investment analytics and wealth-management tools from BlackRock, Addepar, Schwab, and others — AI l
arXiv:2601.16982v2 Announce Type: replace Abstract: Modern generative video models excel at producing convincing, high-quality outputs, but struggle to maintain multi-view and spatiotemporal consisten
arXiv:2609.12744v1 Announce Type: new Abstract: Timely monitoring of coastal water quality is critical for environmental protection, yet conventional satellite workflows rely on downlink and ground pr
arXiv:2609.12932v1 Announce Type: new Abstract: Proposed governance framework for autonomous robotic systems, introducing a three-layer compliance architecture (ARC) instantiated through model safety
So we’re seeing how Anthropic and OpenAI are gunning for regulations. I think most of us realize that this is a ploy for them to achieve regulatory capture, thus securing their moat and kicking out op
arXiv:2609.12498v1 Announce Type: new Abstract: Category-level in-hand manipulation of articulated objects is a formidable yet underexplored challenge for dexterous robotic hands. This difficulty stem
arXiv:2609.13083v1 Announce Type: new Abstract: In urban search and rescue, articulated tracked robots (ATRs) must traverse structured but contact-rich environments such as stairwells and cluttered bu
arXiv:2507.01663v2 Announce Type: replace Abstract: Reinforcement learning (RL) has become a pivotal technology in the post-training phase of large language models (LLMs). Traditional task-collocated
At Anthropic, Claude now writes 80% of our code. Engineers ship 8x more code per quarter. Side effect: Tests grew 10x. CI jobs up 25x in 6 months. Here's what helped us scale: https://claude.com/blog/
arXiv:2502.20386v2 Announce Type: replace Abstract: We address the challenge of task-oriented navigation in unstructured and unknown environments, where robots must incrementally build and reason on i
arXiv:2609.13031v1 Announce Type: new Abstract: With the recent rise and adoption of tabular foundation models, optimizing their inference performance becomes an emerging field for efficiency research
Foundation models made catalog-wide demand forecasting easy; the hard part is now acting on the forecast. This post builds a closed detect-decide-act loop on Databricks and Amazon Quick that reconcile
arXiv:2609.12254v1 Announce Type: new Abstract: The climate literature has grown faster than review teams can read it. That gap matters most for a concept like the environmental social tipping point,
arXiv:2609.12530v1 Announce Type: new Abstract: Autonomous precision milling of biological structures is challenged by incomplete knowledge of target geometry, local material thickness, and critical i
arXiv:2609.13073v1 Announce Type: cross Abstract: Recent breakthroughs in LLM-based systems and their abilities in problem solving and coding have allowed progress in the AI for Science paradigm, pote
ggml-cuda: fallback to F32 on device without BF16 hardware acceleration (#28846) ggml-cuda: fallback to F32 on device without BF16 hardware acceleration: (Nvidia >= AMPERE, AMD >= RDNA3 or = CDNA) app
common : move llama_n_rs_seq to before llama_decode (#28749) This commit moves the llama_n_rs_seq function call to before the llama_decode call and returns directly if the check is true, removing the
sycl : fix oneDNN scratchpad breaking the pool free order (#28704) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/47287268 macOS/iOS: macOS Apple Silicon (
ggml-cpu : disable PCH and fix CACHE_LINE_SIZE ambiguity to fix heap corruption (#28882) Disable the ggml-cpu precompiled header and remove the std::hardware_destructive_interference_size branch from
sycl: rfc: Use radix select for top_k (#28670) sycl: GPU-resident TOP_K for large k, parallelised over the device The SYCL backend refused GGML_OP_TOP_K above k = 32 and let it fall back to the CPU, a
llama.cpp : bump version to 0.4.1 (#28900) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/47376843 macOS/iOS: macOS Apple Silicon (arm64) macOS Apple Silic
ci : add ubuntu-cuda builds to release (#28186) release : add ubuntu-cuda build job (12.8/13.3, x64+arm64) Add GCC 14 for CUDA arm64 builds in CI Eplicit bash Install git for CCCL fetch Install git be
HIP: fattn-mma: use fp32 accumulation on MFMA devices (#28576) use fp32 accumulators in fattn-mma on CDNA Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/47
arXiv:2609.12830v1 Announce Type: new Abstract: Continuous emotion control in text-to-image generation requires a model to improve affective alignment without changing the objects, layout, or scene de
Banger paper from Meta. This work shows that byte-level models start out behind token models and then pass them as compute grows. They show this for distilled 1B models trained on up to 1 trillion byt
Edit: Spelled Baseten not Base-10 Full episode of this available at https://www.youtube.com/watch?v=PrSf7IOYu-I It's interesting to see how Dwarkesh has had to come around to the evidence that we are
arXiv:2609.12188v1 Announce Type: new Abstract: This paper presents a battery-aware predictive trajectory-planning and control framework for multirotors operating under spatially localized disturbance
arXiv:2609.12894v1 Announce Type: new Abstract: Estimating the 3D center of mass of unknown objects is challenging when grasping is infeasible, geometry is irregular, or mass distribution is uneven. W
arXiv:2609.12896v1 Announce Type: new Abstract: LLM-based agents rely on heterogeneous interaction capabilities to accomplish complex tasks. Existing approaches often distribute these capabilities acr
arXiv:2602.00165v2 Announce Type: replace Abstract: Post-training quantization (PTQ) is a practical way to reduce the memory footprint of large language models, but low-bit quantization is sensitive t
arXiv:2609.13057v1 Announce Type: new Abstract: Deep neural networks are expressive enough to contain worst-case targets that can be evaluated in polynomial time but cannot be learned in polynomial ti
This guide identifies six leading knowledge‑engine platforms in 2026—Pinecone Nexus, Databricks Genie, Snowflake Cortex, Microsoft IQ, Palantir Foundry, and Glean—that each transform heterogeneous dat
arXiv:2609.12892v1 Announce Type: new Abstract: Accurate biomedical image segmentation requires not only high global overlap but also reliable delineation of clinically meaningful boundaries. In blood
arXiv:2609.12668v1 Announce Type: new Abstract: Recent deepfake detection studies increasingly suggest remote photoplethysmography (rPPG) signals as an authenticity cue. However, existing benchmarks l
arXiv:2609.12099v1 Announce Type: new Abstract: Classical classifier-combination work distinguishes score-level fusion from hard decision-level voting. We revisit this distinction where independently
arXiv:2609.12403v1 Announce Type: cross Abstract: Cognitive Diagnosis Models (CDMs) play a pivotal role in personalized online learning. Traditional CDMs rely on discrete, ID-based embeddings to repre
arXiv:2609.12437v1 Announce Type: new Abstract: Adaptive RAG often uses retrieval-time signals to decide whether another retrieval, reranking, or multimodal step should run. We ask whether these signa
Do you have something you'd like to share with the r/LocalLLaMA community. This is the place for it! Recommendation on presentation: Please share plain english description of what your project does an
arXiv:2510.26046v3 Announce Type: replace-cross Abstract: Class imbalance complicates probabilistic classification because standard training objectives emphasize majority-class performance. Synthetic
arXiv:2602.13177v2 Announce Type: replace-cross Abstract: The performance of online mirror descent depends critically on the geometry induced by its mirror map, yet standard algorithms largely rely on
arXiv:2604.05793v2 Announce Type: replace-cross Abstract: In LLM agent pipelines, prompt privacy risk propagates beyond a single model call: raw user content enters retrieval queries, memory writes, t
arXiv:2609.12303v1 Announce Type: new Abstract: Small models are made more capable through distillation from a larger one that shares their tokenization scheme. However, do distilled byte and token mo
arXiv:2609.12641v1 Announce Type: new Abstract: Robot foundation models achieve strong in-distribution performance but often degrade under visual distribution shifts. When learning to generate actions
arXiv:2609.12218v1 Announce Type: cross Abstract: The growing use of electroencephalography (EEG) motivates automated analysis that is accurate, transferable, and deployable on constrained hardware. R
arXiv:2609.12454v1 Announce Type: new Abstract: Vision-Language Models such as CLIP enable effective few-shot medical anomaly detection (AD) via strong image-text semantic alignment. However, their gl
Artificial intelligence-powered construction management startup Buildots Ltd. said today it has raised 130 million in new late-stage funding to expand its platform and capitalize on rising investment
arXiv:2609.12575v1 Announce Type: new Abstract: Ambiguity is often treated as a bug for AI systems to resolve---but in human communication and culture, ambiguity can also be a generative resource. Fro
arXiv:2609.12162v1 Announce Type: cross Abstract: Draft-verify-revise is a common LLM orchestration pattern for scaling inference-time compute. One LLM drafts, a second critiques the draft and provide
arXiv:2504.07133v2 Announce Type: replace-cross Abstract: We revisit the problem of estimating k linear regressors with self-selection bias in d dimensions with the maximum selection criterion, as int
arXiv:2609.12002v1 Announce Type: new Abstract: LLMs are increasingly used as automated judges for model training and evaluation, yet individual judges exhibit systematic biases that undermine reliabi
Can you even imagine the nation state level attacks METR & other eval orgs will come under? Eval orgs also need world class cybersecurity as well as AI talent to do this right, they are not overlappin
arXiv:2609.13060v1 Announce Type: new Abstract: Diffusion Language Models (DLMs) offer promising parallel generation capabilities but lag behind autoregressive models in complex reasoning and tool-use
arXiv:2606.23189v2 Announce Type: replace-cross Abstract: Computer-use agents (CUAs) now act on a user's behalf across personal applications such as email, calendars, and to-do lists. This cross-appli
C/C++ provide direct hardware and memory control with near-zero overhead, delivering the raw speed needed for extreme performance work like AI training stacks. Higher-level languages add layers that c
arXiv:2609.12365v1 Announce Type: new Abstract: In the VTaC benchmark 71% of ventricular-tachycardia alarms are false, but silencing a real one can delay recognition of a dangerous arrhythmia. We refr
arXiv:2609.12014v1 Announce Type: new Abstract: Safe offline reinforcement learning assumes a cost function on every transition. We ask what remains possible when safety can be judged only by comparin
arXiv:2609.12163v1 Announce Type: new Abstract: Existing evaluations of concept unlearning in text-to-image (T2I) diffusion models primarily rely on attack success rates obtained through automated adv
arXiv:2609.12221v1 Announce Type: new Abstract: Maintaining consistency over long spatial and temporal horizons remains a fundamental challenge in large-scale LiDAR SLAM, particularly when integrating
On September 14 2026 (02:41 UTC) Teknium announced that **ChatGPT‑Image‑2.5** is now available on the **Nous Portal**, enabling it to be integrated into the **Hermes Agent**. The model can also be acc
Bloomberg: China's Foreign Ministry criticizes warnings about AI risks, saying “fearmongering, confrontation, and vicious competition ... serve the interests of no one” — China criticized calls from l