model releases

Running unsloth/Qwen3.8-27B-UD-IQ4_XS 262k q4_0 KV + vision on 16GB VRAM @ 80t/s and 1500pp

I get a lot of hate whenever I tell people I run a Q4 quant of Qwen3.8 27B with 262k KV 80t/s with vision, all while running 2 screens on windows on the same card. People seem to think I am lying or m

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Model Releases

S^3R: Fast and Faithful RL Rollouts via Self-Sparse Speculative Decoding

DGX agent

arXiv:2610.13202v1 Announce Type: cross Abstract: Fast rollout generation for long-context reinforcement learning with verifiable rewards (RLVR) requires reducing KV-cache traffic without changing the

model-releasesarxiv-cs-cl

12 Oct 2026

Scalable Circuit Learning for Interpreting Large Language Models

arXiv:2606.16939v2 Announce Type: replace-cross Abstract: A prominent research direction in mechanistic interpretability is learning sparse circuits over LLM components to reveal how they jointly prod

Scalable Learning of Determinantal Point Processes with Kernel-Structured Interactions

arXiv:2610.12829v1 Announce Type: cross Abstract: Determinantal point processes (DPPs) on a finite set are probability models that exhibit repulsion where inter-item similarities are encoded by a posi

Scaling RNA Foundation Models through Iterative Refinement

arXiv:2610.13106v1 Announce Type: new Abstract: Biological function in RNA is encoded across scales, from local sequence motifs to long-range structural dependencies. Conventional RNA foundation model

SelectArena: A Modern Benchmark for Feature Selection on Real-world Tabular Data

arXiv:2610.13644v1 Announce Type: cross Abstract: Selecting a subset of features (columns) from a tabular dataset is a ubiquitous challenge in real-world applications. Industry experts seek to minimiz

Self-Compacting Language Model Agents

model-releasesapple-ml-research

Long agent traces composed of chains of thought and tool calls accumulate stale content that anchor subsequent generations, and eventually outgrow the context window. Existing scaffolds mitigate it wi

Self-Preservation in Language Models

arXiv:2610.12602v1 Announce Type: cross Abstract: Continual learning (CL) seeks to adapt pretrained models while preserving prior capabilities. Yet the tasks supplied for preservation cover only part

SeoulMMOD: A Large-Scale Multimodal Origin-Destination Flow Benchmark

arXiv:2610.13730v1 Announce Type: new Abstract: Origin-destination (OD) flow forecasting supports urban mobility decisions by predicting the volume and patterns of human movement across a city. Most e

separating artifacts from the agent makes sense for sharing and cross-AI collaboration

model-releasesyohei-nakajima--x

separating artifacts from the agent makes sense for sharing and cross-AI collaboration No vendor lock-in for your artifacts. Sites, decks, 3D games, reports, dashboards and galleries. Artifacts on Fly

SmartSalesBench: A Resistance-Aware Multi-Turn Benchmark for Evaluating LLM Sales Agents

arXiv:2610.12975v1 Announce Type: new Abstract: We present SmartSalesBench, the first multi-turn conversational benchmark explicitly designed to evaluate large language model (LLM) sales agents agains

SmolWAM: A Latent World-Action Model for Robotic Manipulation on Edge Devices

arXiv:2610.13740v1 Announce Type: cross Abstract: World-action models (WAMs) predict a robot's actions together with the observations those actions will produce. However, the strongest models rely on

Solving VeriContest with a Lean-Backed Rust Verifier

arXiv:2610.03994v2 Announce Type: replace-cross Abstract: VeriContest is a benchmark of 1007 competitive-programming problems in Rust, each with a Verus specification, a judge-accepted solution, and a

Sources: DeepSeek agrees to lead robotic AI startup Winverse AI's seed funding round of tens of millions of dollars, valuing the startup at ~$400M post-money (Bloomberg)

Bloomberg: Sources: DeepSeek agrees to lead robotic AI startup Winverse AI's seed funding round of tens of millions of dollars, valuing the startup at ~$400M post-money — DeepSeek aims to lead the fir

model-releasestechmeme

Spa-Bench: A Real-Robot Benchmark for Spatial Grounding in Vision-Language-Action Models

model-releasesarxiv-cs-ro

arXiv:2610.12696v1 Announce Type: new Abstract: Vision-language-action models (VLAs) offer a promising route toward general-purpose robotics by transferring semantic knowledge from large-scale vision-

Spanning Diffusion and Flow-based Posterior Sampling via Exact Gaussian Conditioning

arXiv:2610.13812v1 Announce Type: new Abstract: Flow-matching and diffusion models are increasingly used as priors for linear inverse problems, however, most methods are bespoke to one class of trajec

SpireBench: Evaluating Long-Horizon Strategic Play of Agentic Models with Slay the Spire

arXiv:2610.12596v1 Announce Type: new Abstract: Agentic large language models now tackle complex tasks, yet strategic reasoning over long horizons is under-studied: most agentic benchmarks are short a

SqueezeBench: Saturation-Resilient Evaluation of Mathematical Capability

arXiv:2610.13461v1 Announce Type: new Abstract: AI systems are making rapid progress in mathematics, but this progress is hard to measure. Benchmarks of solved problems saturate, and in benchmarks of

Static Gradient Attribution Underperforms a Density-Matched Random Mask on Loss-Based Forgetting Within LoRA B-Matrix

arXiv:2610.12744v1 Announce Type: new Abstract: Parameter-efficient continual learning updates a restricted subset of adapter parameters to incorporate sequential tasks while limiting catastrophic for

strix-llama new branch: prompt processing +21–54% over Vulkan and up to 2.7× over stock ROCm kernel at 128k, same outputs quality

I've been tuning llama.cpp on my Strix Halo box (Radeon 8060S, 128 GB) and the numbers are good enough to share. It's a branch called rdna35-perf on top of halo-box/strix-llama.cpp, a llama.cpp fork a

Structure-Aware Numerical Stabilization for Half-Precision Proximal Policy Optimization

arXiv:2610.13306v1 Announce Type: new Abstract: Local online training on resource-constrained platforms requires low computational and training-state overhead. We study the numerical stability and com

SWE-DeceptionBench: Benchmarking Deceptive Behaviors of LLMs Across the Software Development Lifecycle

arXiv:2610.13626v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used throughout the software development lifecycle. This growing reliance on LLMs raises concerns about

SWE-Duel: Towards a Self-Scaling Arena for Coding Agents

arXiv:2610.12569v1 Announce Type: new Abstract: Static coding benchmarks are fixed at release. Over time their tasks leak into training data, and stronger agents eventually saturate them. We argue tha

TabMF: Learning Dataset Representations with Tabular Foundation Models

arXiv:2610.13818v1 Announce Type: new Abstract: Representations of supervised datasets support higher-level machine-learning tasks such as dataset retrieval and distribution-shift monitoring. However,

TabReliBench: Evaluating Tabular Foundation Models Beyond Predictive Accuracy

arXiv:2610.13654v1 Announce Type: new Abstract: Tabular foundation models (TFMs) are increasingly popular for their strong predictive performance. Many also provide posterior predictive distributions

Taking Tokenization off the Host for Agentic LLM Serving

arXiv:2610.13325v1 Announce Type: cross Abstract: Agentic workloads resend long contexts that barely change between calls. Prefix caching now skips most of their prefill, yet every request must still

Task Context Shapes Component Roles in Language Models

arXiv:2610.13895v1 Announce Type: cross Abstract: Large language models reuse the same attention heads across tasks, but identifying these shared heads does not explain what they do differently in eac

Temporal Evidence Forests for Long-Horizon Multi-Party Conversational Memory

arXiv:2610.12874v1 Announce Type: new Abstract: Long-term memory has been widely adopted in LLM-based agents to support persistent interaction and personalized assistance. Long-term multi-party intera

TernaryLLM: Ternarized Large Language Model

arXiv:2406.07177v2 Announce Type: replace Abstract: Large language models (LLMs) have achieved remarkable performance on Natural Language Processing (NLP) tasks, but they are hindered by high computat

Towards Easier-to-Tune Training Algorithms: New Results from AlgoPerf

arXiv:2610.13036v1 Announce Type: new Abstract: Evaluating deep learning optimizer is challenging because confounding factors such as hyperparameter tuning and optimizer-model co-design often obscure

Trainable Quantum-Native Language Models: Dissipative Memory, Capacity Limits, and Hardware Validation

arXiv:2610.12806v1 Announce Type: cross Abstract: We study byte-level autoregressive language models whose hidden state is a small quantum register, whose transitions are learned token-conditioned qua

Trajectory Prediction for Autonomous Driving in Road Construction Zones Using Human-in-the-Loop Driving Data

arXiv:2610.12747v1 Announce Type: cross Abstract: Ego-trajectory prediction in urban roadway work zones remains an underexplored topic in autonomous-driving research, with limited dedicated data and s

Transformer-based In-Context Score Operator Learning for Diffusion Models

arXiv:2610.13690v1 Announce Type: new Abstract: Diffusion models typically learn the generative dynamics of a single target distribution or a family of distributions indexed by conditioning variables

Travel Back To Move Forward: Retrospective Exploration and Evolving for Long Horizon Agents

arXiv:2610.13058v1 Announce Type: new Abstract: Large language model agents increasingly operate in long-horizon environments where early mistakes can trigger cascading failures and trap agents in dea

TreeHCA: Hindsight-Guided Exploration and Credit Assignment for Multi-Turn LLM Agents

arXiv:2610.12828v1 Announce Type: new Abstract: Outcome-supervised group-relative policy optimization (GRPO) assigns the same advantage to every token in an LLM agent trajectory, leaving useful and un

Trusted Data Apps for the Agentic Data Cloud, powered by Looker

model-releasesgoogle-cloud-ai

As a business intelligence user, this probably sounds familiar: Most dashboards only provide you with a standardized canvas and a fixed library of charts, and the “analysis” consists of a CSV export t

TTS-Q: Perception-Guided Post-Training Quantization of Text-to-Speech Diffusion Transformers

arXiv:2610.12474v1 Announce Type: cross Abstract: Zero-shot text-to-speech (TTS) can clone a voice from seconds of audio. Yet the quality comes from billion-parameter diffusion transformers whose size

U-Space: Uncovering When and Why Uncertainty Arises in Language Models [R][D]

model-releasesr-machinelearning

If you build on open-weight reasoning models, you have probably wanted a 'how sure is the model about this answer?' signal that does not cost 5x sampling, a judge model, or a labeled dataset. Hence, w

U4RASD at KnowledgeGraphEval-2026: Ontology-Constrained Encoder and LLM Systems for Arabic Relation Extraction

arXiv:2610.12742v1 Announce Type: new Abstract: This paper details our submission to KnowledgeGraphEval 2026 Subtask 2 on directed Arabic relation extraction. We explored encoder-based and large langu

UkrMeme: Multimodal Explainable Persuasion Detection in Ukrainian Memes

arXiv:2610.13783v1 Announce Type: new Abstract: Memes play a central role in modern online communication, especially in contexts of political conflict where visual and textual cues combine to convey p

Unreliable Narrator Framing as a Cost-effective Mechanism for Satire Explanation of Australian and American Satirical News

arXiv:2610.12863v1 Announce Type: new Abstract: Satirical news is a unique form of misinformation: it is intended to be humorous by the original publication source but can be misinterpreted. Explanati

Unsupervised Multimodal Reward Modeling

arXiv:2610.12707v1 Announce Type: cross Abstract: Vision-language reward models are trained on annotated preference pairs, which are expensive to collect, can disagree, and are ranked by benchmark acc

v0.40.4

model-releasesollama-releases

What's Changed llama: update llama.cpp to b11521 for decision models and EmbeddingGemma 2 by @jmorganca in #18917 server: reuse verified manifests and loaded models in inference routes by @dhiltgen in

VectorDash: A full Windows search replacement incorporating Embeddinggemma-2

Inspired by DigUp for macOS, VectorDash aims to be a full Windows 11 search replacement, powered by EmbeddingGemma 2. Full indexing: search by meaning or exact words across photos, screenshots, audio,

VETR: Execution-Grounded Self-Improving Agent for Symbolic Graphics Reasoning

arXiv:2610.13098v1 Announce Type: new Abstract: Visual agents for symbolic graphics reasoning depend on executable world representations, yet continued improvement remains bottlenecked by ambiguous su

VQIL: Visible Quantum Interference Learning for Perturbation Response Ranking on Graphs

arXiv:2610.13689v1 Announce Type: new Abstract: Learning how local perturbations affect a network is important for identifying which components drive or absorb a system's response. We formulate this a

Weight Clustering Reveals the Importance of Relative Rank in Large Language Models

arXiv:2603.17917v2 Announce Type: replace-cross Abstract: Large language models (LLMs) contain billions of parameters, but many exact weight values are not essential. We apply scalar K-means clusterin

What are you doing for a reliable, well designed local model based AI search?

Ive been using OpenWebUI's inbuilt web search and I can't put my finger on it, but it's not quite as polished, reliable, seamless as using Claude or Gemini. And its often slow beyond a limit that make