model releases

ZOTTA: Test-Time Adaptation with Gradient-Free Zeroth-Order Optimization

arXiv:2603.14254v2 Announce Type: replace Abstract: Test-time adaptation (TTA) aims to improve model robustness under distribution shifts by adapting to unlabeled test data, but most existing methods

25 Aug 2026

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Model Releases

[2608.16157] FreeToken: Efficient Edge-Native MoE Serving with Bandwidth-Adaptive Execution

DGX agent

Source of Claims: https://x.com/Andy_ShuoYang/status/2090856976880472439 Your gaming PC can now serve frontier models at interactive speed using official checkpoints without extreme quantization! Qwen

model-releasesr-localllama

24 Aug 2026

A Critical Audit of Spatiotemporal Forecasting Benchmark Datasets and Baselines

arXiv:2608.20980v1 Announce Type: new Abstract: Graph neural networks (GNNs) are routinely employed for short-range forecasting on multivariate time series with a spatial graph structure. Despite the

A Dataset-Centric Benchmark of Deep Learning Methods for Grape Leaf Disease Classification and Detection

arXiv:2608.20608v1 Announce Type: new Abstract: Grape leaf disease recognition is important for precision agriculture, enabling early diagnosis, timely intervention, and improved vineyard management.

A Modular Agent for Reliable and Auditable Spatial Relation Verification in CT Scans

arXiv:2608.21140v1 Announce Type: cross Abstract: Reliable spatial understanding is an important prerequisite for future medical vision-language systems that aim to support radiological report generat

A VLM Answer Is Not an Anomaly Score: Rank Compression in Training-Free Video Anomaly Detection

arXiv:2608.21244v1 Announce Type: new Abstract: Vision-language models enable training-free video anomaly detection by answering questions about video segments. VAD benchmarks, however, require a scal

A voice dictation tool better than Wispr Flow, Aqua, and Handy( Built for Linux )

Now, some of you might not believe me from the get go, and it's completely fine, But for those who are willing to give Tap a chance, a whole new world of voice dictation is going to unlock for you. Ta

model-releasesr-ollama

AffordAny: Open-World 3D Affordance Grounding from Monocular RGB Images via Vision-Language-Guided Geometric Reasoning

arXiv:2608.20720v1 Announce Type: new Abstract: Open-world 3D affordance grounding requires localizing functional object parts in 3D given free-form language queries. Existing methods typically assume

AgentMercury: Your Agent Can Synthesize Verifiable Environments for Business Scenarios at scale

arXiv:2608.20634v1 Announce Type: cross Abstract: Agents learn to act through interaction with environments, yet the environments used for training are often manually constructed or synthesized around

Aggregate, Don't Adapt: Subject-Level Posterior Aggregation and Transductive Calibration for Cross-Site Parkinsonian Gait Severity

arXiv:2608.20587v1 Announce Type: cross Abstract: We describe the winning entry to the MoCha 2026 Benchmark and Challenge on Parkinsonian Gait, which predicts MDS-UPDRS gait severity from canonicalize

Alabama AG Steve Marshall launches an investigation into OpenAI's security procedures following the Hugging Face breach in July (Cassandre Coyer/Bloomberg Law)

Cassandre Coyer / Bloomberg Law: Alabama AG Steve Marshall launches an investigation into OpenAI's security procedures following the Hugging Face breach in July — Alabama Attorney General Steve Marsha

model-releasestechmeme

Amortized Bandwidth Learning for Kernel Density Estimation under Logarithmic Score

arXiv:2608.20445v1 Announce Type: new Abstract: Kernel density estimation converts finite samples into probability densities, but its performance depends critically on bandwidth selection. Classical s

Annotations as Rollouts: Efficient and Scalable Reinforcement Learning for Video MLLMs

arXiv:2608.20492v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have become a prevailing paradigm for unified video perception. However, post-training on large multi-task data

// Applying Anthropic Primitives at Large Enterprises // Frontier models collapsed the cost of writing custom code. But they did not reduce …

// Applying Anthropic Primitives at Large Enterprises // Frontier models collapsed the cost of writing custom code. But they did not reduce the cost of reviewing and maintaining it. Each bespoke solut

model-releasesdair-ai--x

Applying Anthropic Primitives at Large Enterprises: Harness Paradigm for Knowledge Work

arXiv:2608.20622v1 Announce Type: new Abstract: Frontier models have collapsed the cost of writing custom code: a niche problem a specialist sees in their own domain now costs an afternoon. The cost o

ARQ: Agentic CodeQL Query Refinement for C/C++ Vulnerability Detection

arXiv:2608.20637v1 Announce Type: cross Abstract: Static analyzers have been widely adopted for vulnerability detection in C/C++ programs. Query-based static analyzers (e.g., CodeQL) encode vulnerable

ArtiMo: Agent-Driven Articulated Mesh Animation

arXiv:2608.20699v1 Announce Type: new Abstract: Animating articulated 3D meshes via text requires satisfying strict kinematic constraints, modeling causal interactions between parts, and achieving ins

AsmEvo: Agentic Assembly-Level Optimization of AMD GPU Kernels with Functional Equivalence Verification

arXiv:2608.20711v1 Announce Type: new Abstract: High-performance ML systems increasingly rely on GPU kernels whose editable source is unavailable, generated, or too distant from final machine code to

Asymmetric Capacity Allocation in Self-Refinement Pipelines

arXiv:2608.21345v1 Announce Type: new Abstract: Self-refinement, typically structured as generation, critique, and revision, is a widely adopted paradigm for improving LLM generation and serves as a c

Atom Learning Model (ALM): how a real classroom got tokenised

arXiv:2608.21106v1 Announce Type: cross Abstract: The Atom Learning Model (ALM) tokenises a school curriculum. Two secondary mathematics textbooks were read by machine into 1,934 atoms, each one thing

Automated Trajectory Evaluation for Mobile Agents via Step-Level Consequence Reasoning and Aggregation

arXiv:2608.20797v1 Announce Type: new Abstract: Evaluating language-guided mobile agents has recently shifted from rule-based to model-based approaches to achieve scalable and automated assessments. H

b10604

Deepseek 4: -sm tensor (#26490) DSV4: sm tensor set coarser granularity for head splits fix dspark add model saving for dsv4 + allow dflash to return on specific device add comment about dsv4 seq_rm s

b10605

mamba2 : Flatten in/out projections to dispatch GEMM instead of GEMV (#27513) mamba2 : flatten mamba2 in/out projections to dispatch gemm instead of gemv mamba2 : remove redundant output reshape Websi

b10606

ggml : fix ggml_clamp (#27644) ggml : fix ggml_clamp cont : update ggml-alloc Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/42576162 macOS/iOS: macOS Appl

b10608

mtmd: video: fix moov atom at the end of file (#27596) mtmd: video: fix moov at the end of file Co-authored-by: rkfg rkfg@rkfg.me fix SIGPIPE windows: handle broken pipe case Co-authored-by: rkfg rkfg

b10610

ggml : shorten virtual device naming in CUDA and Metal (#27608) ggml : shorten virtual device naming in CUDA and Metal Assisted-by: llama.cpp:DeepSeek-V4-Flash-0731 ggml-metal : build device descripti

b10612

tests : disable DOTS3NOTE arch test for WebGPU (#27654) Co-authored-by: Stanisław Szymczyk sszymczy@gmail.com Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestation

b10614

metal: per-op source split + parallel compile (#26561) metal : per-op source split + parallel compile (#24021) preliminary extract common header op source split split metallib into 8 libs && load in p

b10615

metal : per-device tuned (Q, NE) for flash-attn vec (#26570) metal : per-device tuned (Q, NE) for flash-attn vec (#25750) rebase Q-generic FA vec body from 01dc936 (#23114) add 53 f16 (Q,NE) flash-att

BackDFL: A Unified Benchmark For Backdoor Attacks and Defenses In Decentralized Federated Learning

arXiv:2608.21137v1 Announce Type: new Abstract: Decentralized Federated Learning (DFL) promises trust-free collaborative learning by replacing the centralized parameter server with peer-to-peer model

Bart- A vintage llm [R]

model-releasesr-machinelearning

after 3 months and 800 burned... Unbounded Labs is proud to introduce Bart, our vintage LLM: 2.82B parameters trained from scratch on 20.1B tokens of English written before 1931. You can talk to it ri

Bart: A vintage llm

BC-Bench: Evaluating Agentic Engineering in a Domain-Specific Language for ERP

arXiv:2608.20851v1 Announce Type: cross Abstract: Agentic engineering systems have shown strong performance on general-purpose benchmarks, yet their effectiveness in enterprise resource planning (ERP)

Belief Without Behavior: Measuring the Translation of Theory of Mind into Coordinated Social Action in Vision-Language Models

arXiv:2608.20975v1 Announce Type: new Abstract: Effective social interaction requires agents to translate mental state inferences into coordinated behavioral signals across verbal and nonverbal channe

[Benchmark] llama.cpp batch/ubatch impacts on PP and TG

My test is running DeepSeek v4 Flash 0731 at native size on DGX Spark machine (GB10, 128 GB unified memory). The model size is bigger than RAM, so weights will be loaded many times when running. To im

[Benchmark] Optimal DFlash2 quants for speed and context size, 5090 RTX, llama.cpp, Qwen 3.8 27B Dynamic3 Unsloth. Comparison with MTP

Graph: A cumulative metric of Speed x Context Size - the higher the dot - the better. Helpful for looking for the most balanced solution. The research relies on DFlash2 Q2 work by AnalogAlok: https://

Benchmarking noisy label detection methods

arXiv:2510.16211v2 Announce Type: replace Abstract: Label noise is a common problem in real-world datasets, affecting both model training and validation. Clean data are essential for achieving strong

Benchmarking Patent Drafting from Inventor-Style Disclosures

arXiv:2608.21249v1 Announce Type: new Abstract: While recent large language models (LLMs) have achieved promising results on individual patent drafting tasks, they fundamentally fail to investigate th

Best model for 16gb ram Mac

Hi everybody! Every now and then these days, we’re seeing really huge open-weight models popping up. But since not everybody has a DGX Station at home, I’m interested in really small models. It’s incr

Beyond End-to-End Success: Diagnosing Failures in Long-Horizon Security LLM Agents

arXiv:2608.20563v1 Announce Type: cross Abstract: Long-horizon security LLM agents must carry information and decisions across many dependent interactions, where later actions often depend on services

Beyond Endpoint Gains: A Weight-Delta Audit of Medical Specialization

arXiv:2608.20768v1 Announce Type: new Abstract: Specialist language models are usually understood through endpoint gains: the generalist scores lower, the specialist scores higher, and the difference

Beyond Imitation: Self-Improving Robot Policies via Off-Policy Q-Planning

arXiv:2608.21204v1 Announce Type: cross Abstract: Behaviour Cloning (BC) has driven remarkable progress in robot manipulation, yet it is fundamentally limited by its inability to self-improve: a polic

Beyond Raw Transcripts: Structured Persona Extraction for LLM-Based Digital Twins

arXiv:2608.20344v1 Announce Type: new Abstract: LLM-based 'digital twins' aim to simulate how an individual would behavein new environments or respond to novel questions, given some representation of

Breaking High Confidence: Practical Face Impersonation under High-Security Thresholds

arXiv:2608.20884v1 Announce Type: new Abstract: Face recognition systems (FRSs) are increasingly deployed in critical real-world services for authentication, such as banking applications and airport i

Building and Evaluating a Synthetic Bengali Speech Resource for Telecom Customer Care

arXiv:2608.20346v1 Announce Type: new Abstract: Speech systems used in customer-facing applications often require domain-specific language coverage. We present a synthetic Bengali speech dataset for t

Can Legal AI Know When It Is Wrong? And Do Students Know When It Is?

arXiv:2608.21089v1 Announce Type: new Abstract: Integrating Large Language Models (LLMs) into the Indian judiciary promises access to justice but introduces severe risks. We identify the 'inertia of c

Can Scientific Claims Be Removed from Large Language Models? A Systematic Evaluation of Claim-Level Unlearning

arXiv:2608.20960v1 Announce Type: new Abstract: Language models (LMs) are trained on static scientific corpora, whereas scientific knowledge continuously evolves through correction and revision. Scien

Capturing Cardiac Cyclicity through Phase-Equivariant Self-Supervised Learning

arXiv:2608.21147v1 Announce Type: new Abstract: The cyclic structure of physiological processes offers a natural prior for self-supervised representation learning, and the cardiac cycle provides a par