Knowledge catalogue
Anthropic: Anthropic releases findings from a pilot that let three external researchers run studies on Claude usage; one study found users delegate high-stakes tasks — Earlier this year, we ran a pilo
Will Knight / Wired: Anthropic releases Model Hardware Standard, a framework to help AI agents use physical systems like microscopes, quantum computing hardware, and robot arms — The potential for AI
On Thursday, a judge ruled that the Pentagon's blacklisting of Anthropic earlier this year was unconstitutional, delivering the AI lab a win in a monthslong rollercoaster of a battle with the Trump ad
arXiv:2608.25830v1 Announce Type: new Abstract: Global Tensor Motion Planning (GTMP) solves motion planning with batched tensor operations over a layered multipartite graph. We generalize GTMP so that
arXiv:2608.25089v1 Announce Type: new Abstract: Crosslingual evaluation of language models that enables fair comparisons remains a fundamental challenge in multilingual NLP. Existing studies adopt a v
arXiv:2608.25727v1 Announce Type: new Abstract: Large language models (LLMs) have recently advanced graph neural networks (GNNs) by enriching node representations with semantic information, giving ris
arXiv:2510.20803v2 Announce Type: replace Abstract: We propose a novel AutoRegressive Generation-based paradigm for image Segmentation (ARGenSeg), achieving multimodal understanding and pixel-level pe
arXiv:2608.25520v1 Announce Type: new Abstract: Audio-visual cross-modal Fine-Grained Visual Categorization (FGVC) aims to identify fine-grained categories by jointly leveraging visual and auditory in
arXiv:2608.26004v1 Announce Type: cross Abstract: Agentic LLM pipelines face escalating inference costs as context accumulates across retrieval, tool use, and multi-turn interactions. To control laten
audio.cpp 0.7 is out :) This release adds a lot of new audio models and a new way to compare them locally. Audio.cpp is now at 62 model families and 85+ model variants. And it keeps growing! The bigge
arXiv:2608.25948v1 Announce Type: new Abstract: Medical image foundation models can predict clinical phenotypes from computed tomography (CT), but strong performance leaves open whether they read dise
// Automata from agent traces // How much of your agent's behavior comes from the model, and how much from the harness you wrapped around it? New work collapses an entire corpus of agent traces into a
arXiv:2608.25465v1 Announce Type: new Abstract: Visual inspection of welded assemblies remains one of the least automated stages in many industrial production processes, still depending largely on the
arXiv:2608.25637v1 Announce Type: new Abstract: Reference-based verifiers are important for evaluating reasoning models and providing accurate outcome rewards in reinforcement learning with verifiable
arXiv:2608.25618v1 Announce Type: new Abstract: Long-document visual question answering increasingly relies on VLM agents that retrieve candidate pages, inspect page images, write findings to working
hexagon: support for multi-NPU devices (IQ9, IQ10) and fully asynchronous backend (#26501) hexagon: use non-host bufs by default and make the backend fully async hex-hb: remove optional hostbuf suppor
models : support nanbeige4.2-3B (#27730) Co-authored-by: admin lizongqiang@kanzhun.com Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/43308396 macOS/iOS: m
llama : add --n-cpu-ffn option (#26622) common : dedupe --n-cpu-moe / --spec-draft-n-cpu-moe override loops common : add --n-cpu-ffn to CPU-offload dense FFN weights of first N layers common : general
metal : fix memory leaks due to missing autoreleasepools (#27758) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/43372015 macOS/iOS: macOS Apple Silicon (a
args: add --video-* CLI arguments (#24318) args: add --video-* CLI arguments gen docs nits add mtmd_helper_init_opt Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attes
model : simplify MiniMax-01 graph (#27790) Co-authored-by: Stanisław Szymczyk sszymczy@gmail.com Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/43387702 ma
spec: Add benchmark-only synthetic speculative acceptance options (#27711) Add benchmark-only synthetic speculative acceptance to llama-server and llama-cli Address review comments Address review comm
llama: model_loader: add TENSOR_READ_LAZY (#27794) llama: model_loader: add TENSOR_GET_ROW_LAZY add --tensor-read-lazy rename to TENSOR_READ_LAZY gen docs address comments Website: https://llama.app A
Feature: Added LIGHTNING_INDEXER support for Deepseek V4 ops on Vulkan Backend (#27453) vulkan: add LIGHTNING_INDEXER op vulkan: updated lightning_indexer.comp and ggml-vulkan.cpp with 128-lane dot-pr
quantize: cap working memory size to avoid loading big tensors onto RAM (#27795) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/43468853 macOS/iOS: macOS A
opencl: add bin kernels kernel_gemm_moe_q4_0_q8_1_dp4a_bin, kernel_gemm_moe_mxfp4_q8_1_dp4a_bin (#27768) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/434
spec : add DFlash2 support (local convolution + candidate selector) (#27342) (#27816) spec : add DFlash2 support (local convolution + candidate selector) (#27342) support DFlash2 Add p_min in DFlash2
ci : bundle HIP runtime DLLs with Windows ROCm release (#26973) Copy amdhip64_7, amd_comgr and rocm_kpack next to the binaries so the correct HIP runtime loads over the driver's copy in System32. Fixe
model: add Qwen3.8-Flash-Next (qwen4exp) (#27742) gguf: add qwen4exp (Qwen3.8-Flash-Next) arch and converter Adds the GGUF-side plumbing for HF model_type qwen4_exp: MODEL_ARCH.QWEN4EXP plus tensors f
ci : build only the ggml-hip backend for windows-rocm release (#27753) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/43506547 macOS/iOS: macOS Apple Silic
server: add ctx-per-slot (--kv-unified-per-slot) (#24124) Add ctx-per-slot argument for unifid KV cache Swap out ctx fractions for ctx pool slots Formatting cleanup Remove ctx-pool-slots, make ctx-per
hex-unary: fix RMS_NORM_MUL weight-offset bugs for grouped/broadcast norms (#27798) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/43526462 macOS/iOS: macO
ggml-hexagon: add HTP unary ops for ABS and LOG (#27786) Add HVX-accelerated implementations for GGML_OP_LOG and GGML_UNARY_OP_ABS on the HTP backend. Register HTP_OP_UNARY_ABS and HTP_OP_UNARY_LOG in
arXiv:2502.16744v3 Announce Type: replace Abstract: In adversarial Constrained Online Convex Optimization (COCO), a learner selects actions from a fixed convex set while seeking both low regret and lo
arXiv:2608.25190v1 Announce Type: new Abstract: Fake news detection has become an important Natural Language Processing (NLP) task due to the rapid spread of misinformation through online news platfor
arXiv:2509.06346v3 Announce Type: replace Abstract: Sparse Mixture-of-Experts (MoE) has become a key architecture for scaling large language models (LLMs) efficiently. Recent fine-grained MoE designs
arXiv:2608.25163v1 Announce Type: new Abstract: Offline reinforcement learning (RL) leverages static datasets to learn decision policies without real-time environment interaction. While recent sequenc
arXiv:2608.25761v1 Announce Type: new Abstract: One common trade-off in the use of large language models involves reducing the size of the model while increasing the amount of computation at inference
arXiv:2608.25028v1 Announce Type: new Abstract: Spoken-language analysis via prompt-based domain-adaptive models is a promising direction for low-resource, non-invasive dementia screening, but such mo
arXiv:2608.25152v1 Announce Type: new Abstract: Multi-agent LLM systems increasingly debate answers, coordinate research, simulate users, and mediate information flows, making agent-to-agent persuasio
arXiv:2608.26035v1 Announce Type: new Abstract: When a speaker refers to a scene that the listener cannot directly see, the listener must decide whether to preserve its current understanding or revise
arXiv:2608.25551v1 Announce Type: new Abstract: Stochastic gradient descent (SGD) is typically analyzed at a deterministic horizon chosen before the algorithm is run, even though practical stopping de
arXiv:2608.25350v1 Announce Type: new Abstract: Vision-language models (VLMs) have emerged as a powerful source of supervision for reinforcement learning, enabling agents to leverage rich semantic kno
arXiv:2608.25570v1 Announce Type: new Abstract: Hardware kernel optimization requires repeated compilation, correctness testing, profiling, and revision. LLM agents can automate parts of this process,
arXiv:2608.24953v1 Announce Type: cross Abstract: Protein fitness landscapes contain nonlinear interactions in which mutation effects depend on other residues. We introduce ORBIT, an Order-Resolved Be
arXiv:2602.14071v3 Announce Type: replace-cross Abstract: Driving fatigue is a major contributor to traffic accidents and poses a serious threat to road safety. Electroencephalography (EEG) provides a
BIG ANNOUNCEMENT FROM HUGGING FACE TODAY: We're unveiling Microduck 🐥🤖 It's a tiny $399 open-source robot you can teach new tricks with reinforcement learning. It can walk, pick things up, get back up
Microsoft Corp. co-founder Bill Gates has sounded the alarm regarding how artificial intelligence will cause profound disruption in the labor market, warning that millions of jobs are at risk and ther
arXiv:2511.19972v4 Announce Type: replace Abstract: Recently, Reinforcement Learning with Verifiable Rewards (RLVR) has emerged as an effective approach to incentivizing reasoning capability in Large
arXiv:2608.25418v1 Announce Type: new Abstract: Progress in 4D LiDAR segmentation is bottlenecked by data. Assigning temporally consistent labels across sparse point cloud sequences is costly and hard
Breaking Claude Code Opus 5 Auto Mode Anthropic are putting a great deal of faith in Claude Code's auto mode for protecting their coding agent users against prompt injection attacks. They recently mad
Breaking News: The World’s FIRST Microducks football tournament! Only in SF. @ClementDelangue, @PollenRobotics, @Thom_Wolf, @huggingface Let’s make it happen… Media We have a huge news to share today!
arXiv:2502.02118v2 Announce Type: replace-cross Abstract: Self-supervised learning has been a powerful approach for learning meaningful representations from unlabeled data across various domains, redu
Creative teams produce more assets than ever, but fragmented tools and manual context transfer slow production. This post shows how to build a reusable agent harness with Amazon Quick and fal, connect
arXiv:2608.25419v1 Announce Type: cross Abstract: Beyond-visual-range (BVR) air combat is a challenging reinforcement-learning domain characterized by partial observability, long-horizon decision maki
arXiv:2608.24958v1 Announce Type: cross Abstract: An audio language model is a black box in a specific way: we see what it says, never what it works out on the way there, and chain-of-thought monitori
arXiv:2608.25148v1 Announce Type: new Abstract: Frozen hematology foundation-model (FM) embeddings reach near-saturated in-domain white-blood-cell (WBC) accuracy, but clinical deployment demands relia
arXiv:2608.25813v1 Announce Type: new Abstract: For overparameterized neural networks, many solutions can fit the training data equally well while behaving very differently on unseen samples. Grokking
arXiv:2608.25371v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) has become a prevalent paradigm for scaling Vision Transformers efficiently. To ensure computational scalability and prevent ex
arXiv:2608.26000v1 Announce Type: cross Abstract: Wearable electrocardiogram (ECG) and photoplethysmogram (PPG) sensors are complementary but individually fragile: motion artifact, poor contact, and s