model releases

Strata with Qwen3.8 Flash Next UD-Q4_K_XL

model-releasesr-localllama

Been seeing quite a few posts about Strata lately, so I figured I'd give it a shot on my RTX PRO 6000 and I am very impressed. Most of the benchmarks I've seen are using IQ2 or IQ3 quants, so I wanted

10 Oct 2026

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The ultimate LLM benchmark: Chilean Spanish. 80% of AI models fail to recognize Chilean Spanish and insist on speaking like an Argentine

DGX agent

The ultimate LLM benchmark: Chilean Spanish. 80% of AI models fail to recognize Chilean Spanish and insist on speaking like an Argentine 80% de modelos de IA no logra reconocer el español chileno e in

model-releasescristobal-valenzuela--x

10 Oct 2026

We @Sequoia are thrilled to back @TypesafeAI @CompleteSkeptic. ChatGPT put AI front and center in the consumer mind. Claude Code transformed…

model-releasessonya-huang--x

We @Sequoia are thrilled to back @TypesafeAI @CompleteSkeptic. ChatGPT put AI front and center in the consumer mind. Claude Code transformed the day-to-day work of the developer/knowledge worker. Jev

10 Oct 2026

3BASiL: An Algorithmic Framework for Sparse plus Low-Rank Compression of LLMs

arXiv:2603.01376v2 Announce Type: replace Abstract: Sparse plus Low-Rank (mathbf{S} + mathbf{LR}) decomposition of Large Language Models (LLMs) has emerged as a promising direction in model compressio

4-Tensor Attention Model for Semantic Physical Reality

model-releasesarxiv-cs-cl

arXiv:2610.11716v1 Announce Type: cross Abstract: We describe a 4-tensor attention model that predicts the next semantic state of a scene, for video generation and robot planning. A window of states h

A 3D Characterization Framework for Intelligent Sequential Decision Making

arXiv:2610.11696v1 Announce Type: new Abstract: Puzzles are widely used to evaluate the reasoning capabilities of artificial intelligence (AI) systems for sequential decision making, yet approaches or

A Camera-Native Stereo VR180 Dataset

model-releasesarxiv-cs-cv

arXiv:2610.10607v1 Announce Type: new Abstract: Immersive VR180 video is increasingly produced with professional stereo fisheye cameras, yet public VR180 research resources are mostly collected from o

A Closer Look at Agentic BBO: Benchmarking LLM Agents for Black-Box Optimization

arXiv:2610.12183v1 Announce Type: cross Abstract: Black-box optimization (BBO) arises in many scientific and engineering problems where objective evaluations are expensive and limited. Recent large la

A Dual-Hypothesis Reasoning Framework for LLM Guardrails

arXiv:2607.17575v3 Announce Type: replace Abstract: We propose ARBITER, a novel LLM guardrail framework that introduces two key ideas: (i) dual-hypothesis reasoning, a reasoning method for LLM guardra

A mesh-based neural energy method for the simulation of heterogeneous composites

arXiv:2610.10862v1 Announce Type: cross Abstract: Modeling heterogeneous materials remains a challenge for physics-informed neural networks such as the deep energy method (DEM). The DEM and its varian

A new feature for my blog, built using my voice

model-releasessimon-willison

I shipped a new feature for my blog today: the Newsletters page, which offers an index of all of the newsletters I've sent out, both my free weekly Substack and my monthly sponsors-only updates. I bui

A Survey on LLM-Integrated Hardware Design Verification

arXiv:2610.10580v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly being integrated into hardware verification to automate specification interpretation, verification-artif

A Unified Score Matching Paradigm for Video Anomaly Detection and Anticipation

model-releasesarxiv-cs-cv

arXiv:2610.11149v1 Announce Type: new Abstract: Video anomaly detection (VAD) is a fundamental and safety-critical task in computer vision. Recent generative approaches detect anomalies from a distrib

A week of free access to Qwen3.8-Max, Qwen3.8-Flash, and Wan3.0 on @gmi_cloudis live. Explore what you can build with us now. 🙌

A week of free access to Qwen3.8-Max, Qwen3.8-Flash, and Wan3.0 on @gmi_cloudis live. Explore what you can build with us now. 🙌 We're extending FREE Qwen 3.8 Max + Flash for 7 more days! And we've inc

model-releasesqwen--x

Accurate and Efficient Object Pose Estimation via the Aggregation of Diffusion Features

model-releasesarxiv-cs-cv

arXiv:2403.18791v4 Announce Type: replace Abstract: Estimating the pose of objects from images is a crucial task of 3D scene understanding, and recent approaches have shown promising results on very l

ActionCodec: What Makes for Good Action Tokenizers

arXiv:2602.15397v2 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models leveraging the native autoregressive paradigm of Vision-Language Models (VLMs) have demonstrated superior

AdaCast: Conditional Parameter Generation for Adaptive Time Series Forecasting

arXiv:2610.12240v1 Announce Type: cross Abstract: Time-series foundation models (TSFMs) have achieved strong forecasting performance across domains. However, most adaptation methods remain static. Exi

Adapting English Quality Classifiers for Multilingual LLM Pretraining Data Selection

arXiv:2610.11585v1 Announce Type: cross Abstract: Recent advances in large language model (LLM) pretraining highlight the role of high-quality training data in improving performance. While model-based

AdaptLSTM: Efficient Adaptive Online Learning for Cloud Workload Forecasting under Distribution Drift

arXiv:2610.12265v1 Announce Type: new Abstract: Accurate workload forecasting is critical for elastic resource provisioning in web-scale cloud services, where distribution shifts driven by viral conte

Agent4RE: A Self-Refining Multi-agent Framework for End-to-End Software Requirements Engineering and Benchmarking

arXiv:2610.10628v1 Announce Type: cross Abstract: Existing LLM-based approaches for software Requirements Engineering (RE) typically rely on basic prompting strategies or rudimentary agent collaborati

AgentHorizon: Evaluating Agentic Judges for Long-Horizon Computer-Use Tasks

arXiv:2610.11050v1 Announce Type: new Abstract: Computer-use agents are capable of completing complex tasks, increasing the use of automatic judges to determine success, either for training or for eva

Agentic-TTT: Training test-time policy for test-time training

arXiv:2610.12002v1 Announce Type: cross Abstract: Test-time training (TTT) adapts an LLM's parameters using signals derived from test inputs, and can make striking improvements in pre-specified settin

AgentTime: Can Agents Estimate and Control Their Own Runtime?

arXiv:2610.09944v2 Announce Type: replace Abstract: An essential control of AI agents is their ability to manage runtime. This ability requires a sense of time-awareness, to predict and estimate wall-

Amortized Off-Policy Evaluation for LLMs

arXiv:2610.10848v1 Announce Type: new Abstract: Accurate evaluation is central to selecting which LLM to deploy, yet testing a candidate on live traffic exposes real users to an unvetted model. Teams

An Explainable Header-Centric Framework for Large-Scale Semantic Table Interpretation and Data Quality Assessment

arXiv:2610.10541v1 Announce Type: new Abstract: Knowledge Graph (KG) quality depends not only on downstream graph validation, but also on the quality of tabular metadata used before integration. In me

Anthropic’s AI gave Philadelphia police a fake tip about an unsolved homicide

model-releasesthe-verge-ai

An Anthropic AI model provided false information about an unsolved homicide to a Philadelphia Police Department (PPD) tipline, according to a report from 6abc. In a statement released on Friday, the P

Arbiter: Detecting Interference in LLM Agent System Prompts

arXiv:2603.08993v2 Announce Type: replace-cross Abstract: System prompts for LLM-based coding agents are software artifacts that govern agent behavior, yet lack the testing infrastructure applied to c

ASPIRE: Saddle-Point Discovery through Set Prediction and Physical Refinement

arXiv:2610.10969v1 Announce Type: new Abstract: Predicting thermally activated diffusion and defect evolution with event-driven models requires identifying atomic rearrangement mechanisms and their ac

b11516

hexagon: fix IM2COL patch-embed DMA ring overflow (#30189) hexagon: fix IM2COL patch-embed DMA ring overflow The exact-tiling (stride == kernel, no pad/dilation) IM2COL DMA kernel issues ICKH DDR->VTC

b11517

CUDA: pass src1 precision to host MMQ config helpers (#30168) CUDA: pass src1 precision to host MMQ config helpers Signed-off-by: ynankani ynankani@nvidia.com make src1 prec explicit Signed-off-by: yn

b11518

metal: add the 128/96 flash attention kernels, accept every compiled pair (#30209) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/54260937 macOS/iOS: macOS

b11521

server: use port 9931 by default (#30159) server: use port 9931 by default revert unrelated changes Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/54269123

b11523

ci: fix Models Backend webgpu by supporting GGML_OP_DUP (#30216) The mixed batch path of PR-29622 writes the token rows with set_rows into a dup of the embeddings. WebGPU did not support DUP, so the d

b11524

musa: drop mp_21 from the default architectures (#30203) musa: drop mp_21 from the default architectures Signed-off-by: Xiaodong Ye xiaodong.ye@mthreads.com Address review comments Signed-off-by: Xiao

b11526

vulkan: fix rms_norm workgroup count overflow (#30145) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/54337638 macOS/iOS: macOS Apple Silicon (arm64) macOS

b11527

webgpu: use 2D workgroup dispatch for all the ops which use 1D dispatch (e.g., rms_norm) (#30219) remove 1D workgroups dispatching formatting Website: https://llama.app Attestations: https://github.co

b11528

meta : handle host views (#30217) meta : handle views of tensors allocated on the host A view shares the memory of its view_src, so ggml-alloc never allocates a view in the buffer of the split it land

b11529

ggml: fix OOB write in ggml_acc with negative offset (#30135) ggml_acc_impl narrowed a size_t offset to int32_t without checking that it fits, so a large offset could truncate to a negative int32_t. T

b11530

llama: keep the backend sampling graph static across ubatches (#30223) The reserve builds n_outputs_max_per_seq sampling chains per sampler, while a decode built one per output row, so the graph chang

b11531

chat : refactor API (#30210) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/54392536 macOS/iOS: macOS Apple Silicon (arm64) macOS Apple Silicon (arm64, Kle

b11532

model : use exact GELU for ModernBERT encoders (#30108) model : use exact GELU for ModernBERT encoders Assisted-by: Codex model : keep tanh GELU aliases on ggml_geglu Assisted-by: Claude Opus 5.5 mode

b11533

opencl: fix kernel compilation for a6x GPUs (#30176) opencl: skip kernel_cpy_f32_f32_pack on A6X to avoid shader compiler crash The A6x compiler backend found in iot device with a623 (E031.50.31.01) c

b11534

CUDA: Remove redundant CUDA copies after SSM_SCAN (#29807) CUDA: fuse copy of updated state snapshots into recurrent cache with ssm_scan CUDA: remove redundant cuda copies with K==1 (non spec-dec) sce

b11535

llama-bench: respect -fitc if bigger than required benchmark size (#28331) Assisted-By: opencode,llama.cpp,Qwen3.6-35B-A3B,Qwen3.8-27B Website: https://llama.app Attestations: https://github.com/ggml-

b11537

graph : reorder get_rows for embeddings (#30160) graph : reorder get_rows for embeddings cont : fix gemma4 and improve input embedding construction logic cont : add TODO for lora cont : fix raw embedd

b11538

CUDA: fix round issue, under MSVC the CPU and GPU agree (#30229) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/54453988 macOS/iOS: macOS Apple Silicon (ar

b11539

vendor: apply deep nested json patch from upstream (#30253) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/54488539 macOS/iOS: macOS Apple Silicon (arm64)

Banger paper from Meta Superintelligence Labs on self-improving agents. (bookmark it) It's hard to know exactly what drives self-improvement…

Banger paper from Meta Superintelligence Labs on self-improving agents. (bookmark it) It's hard to know exactly what drives self-improvement, since so many variables are at play (notes, skills, tool c

model-releasesdair-ai--x