Knowledge catalogue
Learn how Azure AI Speech LLM 2607 improves multilingual and mixed-language recognition, lowers latency, and simplifies domain-specific customization with enhanced phrase lists. The post Announcing Az
Another brilliant paper from Meta. This one is worth reading if you work on production-grade ranking or recommendation systems. Meta deployed an autonomous agent that runs the ML iteration cycle acros
Another goated release by DeepSeek. Open weight, btw. Outperforms Opus 5 on key benchmarks, btw. Lower prices too. Looks like an extremely efficient model. What a legendary run. 🚀 Introducing DeepSeek
Another interesting approach to self-evolve agent skills. But it's important to know that skill self-evolution loops fail in two specific ways: 1. Direction instability. Effective corrections get over
Wall Street Journal: Anthropic details distillation efforts by Chinese companies, like Moonshot and DeepSeek, sending user queries to Claude via “transfer stations” outside China — Anthropic says Deep
Anthropic folk are pretty consistent on their p(Doom). @DarioAmodei is publicly at 25% I think the difference now is that post Navier-Stokes its really, really tough to say AI isn't/won't be smarter t
Gian Volpicelli / Bloomberg: Anthropic gives EU cybersecurity agency ENISA testing access to Mythos 5 after months of talks that began in late May; ENISA still lacks access to Mythos 5.1 — Anthropic P
Anthropic: Anthropic publishes a threat intelligence report on how it disrupted efforts to misuse Claude for cyberattacks, influence operations, surveillance, and more — Cyber operations Surveillance
Individual hackers are now sustaining campaigns that would have needed many skilled operators a year ago, because artificial intelligence has absorbed the labor that used to set state-backed teams apa
arXiv:2609.08861v1 Announce Type: new Abstract: Benchmark scores are a central currency in model releases: they inform purchasing decisions, shape public trust, and influence policy. Yet, a key assump
arXiv:2609.08729v1 Announce Type: new Abstract: The transition from single-core to multi-core architectures in safety-critical embedded systems introduces significant challenges due to inter-core inte
arXiv:2609.09429v1 Announce Type: new Abstract: While accurate measurement of socioeconomic indicators remains challenging in data-scarce regions, which limits policy interventions and resource alloca
arXiv:2609.07712v1 Announce Type: new Abstract: Mobile GUI agents can execute tasks from natural-language instructions, but their evaluation remains difficult to make both realistic and reproducible.
Spoke with many providers who lurk in this sub, plus met folks who work in inference. For a 10k monthly revenue, a provider was able to retain only 200 dollars in profit due to GPU costs. Their custom
arXiv:2609.10193v1 Announce Type: cross Abstract: Protein-protein interaction (PPI) databases do not faithfully reflect biological realities. Instead, they are influenced by study and technical biases
Paris-based Arlequin AI SAS today announced it raised €28 million, about $32 million, in new funding to accelerate development of a new AI model architecture based on a different type of network that
arXiv:2609.09757v1 Announce Type: cross Abstract: Real-time MRI (rtMRI) captures the dynamics of the entire vocal tract during speech, but labeled data are scarce and the modality - single-slice, gray
Like many of you, I have seen many posts and tweets in the last weeks complaining about Artificial Analysis being 'broken', 'meaningless', and 'bought out.' People who say this have done no research a
arXiv:2609.08105v1 Announce Type: new Abstract: The Indonesian Digital Library of Culture (Perpustakaan Digital Budaya Indonesia, PDBI; budaya-indonesia.org) is a participatory platform that has colle
arXiv:2609.10489v1 Announce Type: new Abstract: AI literacy provides foundational competencies that support ethical, transparent, and sustainable technological development, although higher-order capab
arXiv:2603.16112v2 Announce Type: replace-cross Abstract: Adapting large language models (LLMs) to specialized financial reasoning typically requires expensive fine-tuning that produces model-locked e
arXiv:2603.01690v3 Announce Type: replace-cross Abstract: While dense biomedical embeddings achieve strong performance, their opaque dimensions limit transparency in biomedical NLP. Recent question-ba
arXiv:2609.10137v1 Announce Type: new Abstract: A hallmark of human dexterity is the cooperative use of fingers, where different fingers take on distinct yet coordinated roles to accomplish fine manip
arXiv:2609.07102v1 Announce Type: cross Abstract: Astronomical spectra encode rich physical information, but drawing scientific conclusions from spectral features typically requires expert interpretat
Identifying the next phase of software development as always-on agentic artificial intelligence, Atlassian plc today announced a new set of upcoming Jira features to help engineering teams run AI agen
arXiv:2609.05802v1 Announce Type: cross Abstract: Large language models answering questions over multi-page documents are expected to cite the supporting pages, yet supplied citations are sometimes in
arXiv:2609.08318v1 Announce Type: cross Abstract: The transition from human-centric assistance to Autonomous Software Engineering (ASE) agents has enabled the resolution of complex real-world SE tasks
arXiv:2405.02228v4 Announce Type: replace-cross Abstract: Large language models (LLMs) increasingly generate citation-backed responses, yet citation hallucination remains a major challenge for trustwo
arXiv:2510.11454v2 Announce Type: replace-cross Abstract: Recent advancements in large multimodal models (LMMs) have shown strong capabilities in audio understanding. However, most systems rely solely
arXiv:2609.09356v1 Announce Type: new Abstract: At Noora Health, our nurses answer more than 50,000 medical queries per month on our WhatsApp-based service that provides caregivers with on-demand supp
arXiv:2609.06783v1 Announce Type: cross Abstract: LLM agents operate in workflows where unsafe actions can have real consequences. Existing safety evaluations often reduce behavior to a single score,
arXiv:2609.06771v1 Announce Type: cross Abstract: Authorship signals matter in settings where writing style carries identity: digital forensics, plagiarism analysis, account linking, misinformation in
arXiv:2609.05446v1 Announce Type: new Abstract: We introduce AutoFyn, an agent harness inspired by the Expert Iteration algorithm, adapting a frozen model across many rounds by updating persistent sta
arXiv:2609.06366v1 Announce Type: new Abstract: Scientific discovery in data-rich domains is currently constrained by human bandwidth: the growth in the volume and complexity of real-world data far ou
arXiv:2609.06879v1 Announce Type: cross Abstract: Steering vectors have rapidly emerged as a popular and effective method for guiding the output of LLMs in very specific ways. But constructing accurat
arXiv:2609.08071v1 Announce Type: new Abstract: Firms making inventory decisions have access to operational data, optimization tools, and large language models (LLMs). Typically, data characterize the
arXiv:2609.10082v1 Announce Type: cross Abstract: Accurate camera intrinsic calibration is fundamental to robot perception, and the accuracy depends on the quality of the collected images. However, ex
arXiv:2609.10366v1 Announce Type: cross Abstract: While AVSR has achieved sub-1% word error rates on the standard LRS3 benchmark, its reliance on broadcast speech obscures whether this reflects true g
arXiv:2609.10024v1 Announce Type: new Abstract: Robot Operating System 2 (ROS 2) standardizes application code against a middleware interface (RMW) whose reference implementations are built on the Dat
model: fix all granite family parameter counts (#28643) model: fix all granite family parameter counts Signed-off-by: Aaron Teo aaron.teo1@ibm.com model: fix additional include, add missing A prefix f
ggml-cpu(s390x): add Q1_0 vector intrinsic support (#28606) ggml-cpu: add ggml_vec_dot_q1_0_q8_0 support Signed-off-by: Aaron Teo aaron.teo1@ibm.com ggml-cpu: clean up variable naming for understandin
ggml-cpu(s390x): add repack support for q4_0 (#28667) ggml-cpu: clean comments Signed-off-by: Aaron Teo aaron.teo1@ibm.com Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cp
vulkan : add command-buffer debug labels for GPU profilers (#28101) vulkan : add command-buffer debug labels for GPU profilers Co-authored-by: gabby-zy z2262718160@gmail.com Assisted-by: Claude Code v
memory : avoid allocating V cache for indexer (it's not used) (#28330) Co-authored-by: Stanisław Szymczyk sszymczy@gmail.com Website: https://llama.app Attestations: https://github.com/ggml-org/llama.
vulkan: fall back to shared-memory reduction for dmmv on PowerVR (#28341) The Imagination proprietary Vulkan compiler returns VK_ERROR_UNKNOWN from vkCreateComputePipelines for every dequant mul_mat_v
tests : drop SYCL special-casing in test-backend-ops.cpp (#28688) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/46555010 macOS/iOS: macOS Apple Silicon (a
tests : increase tolerance for Add fusion tests (#28691) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/46565769 macOS/iOS: macOS Apple Silicon (arm64) mac
models: clean up some dead switch branches in old models (#28669) Some of these if statements were copypastaed in a former refactor and never cleaned up to remove the cases that could never happen any
spec: fix failed to decode mtmd chunk with DFlash (#28587) speculative: fix failed to decode mtmd chunk with DFlash When using DFlash w/ vision models, the drafter memory fails to allocate new tokens
ci : Update WoA CUDA 13.4 release to use 13.4.1 GA redistributables (#28687) Move Windows ARM64 CUDA 13.4 builds from the Developer Preview archives to the 13.4.1 GA redistributables Website: https://
vulkan: small M matrix optimizations for qwen (#28457) vulkan: optimize m=1 mul_mat by swapping A/B vulkan: Improve small M perf Allow split_k with small M. Make small vs med tile selection (for coopm
vulkan: use add_alloc_dep to enable topk_moe fusion for prefill (#28422) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/46661423 macOS/iOS: macOS Apple Sil
vulkan: use CPU writes in ggml_backend_vk_cpy_tensor_async if the context is idle (#28618) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/46709648 macOS/iO
arXiv:2609.07766v1 Announce Type: cross Abstract: Assessing suicide risk from social media text is a small-data, high-stakes setting requiring not only severity prediction but also supporting evidence
arXiv:2609.05794v1 Announce Type: cross Abstract: Open-weight large language models face a low-cost white-box threat from representation engineering attacks. Attackers can estimate refusal directions
arXiv:2603.04199v2 Announce Type: replace-cross Abstract: Theoretical and applied research into privacy encompasses an incredibly broad swathe of differing approaches, emphases and aims. This work int
arXiv:2609.09246v1 Announce Type: cross Abstract: Exploration drill targeting in structurally complex terranes is hindered by sparse sampling, heterogeneous datasets, and the ambiguity of geophysical
arXiv:2608.00745v2 Announce Type: replace Abstract: Modern endpoint detection systems face a fundamental tension: signature-based approaches are trivially evaded by polymorphic or adaptive threats, wh
arXiv:2609.10036v1 Announce Type: cross Abstract: Large language model agents produce fluent action sequences across a wide range of tasks, yet they fail in characteristic ways once the environment be
arXiv:2609.08765v1 Announce Type: cross Abstract: Large language model (LLM) benchmarks are often treated as fixed datasets with stable scores, yet their outcomes depend on configurable evaluation pip