Search: “models”

Heterogeneous Structured Pruning Under Resource Constraints for Hardware-Efficient Large Language Models

arXiv:2610.15781v1 Announce Type: new Abstract: Training-free pruning removes weights from pretrained large language models to reduce their deployment cost. However, existing approaches typically cons

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Tutorials

In-Context Learning Can Help Vision-Language Models Overcome Training Priors

DGX agent

arXiv:2610.12942v2 Announce Type: replace Abstract: Vision-language models (VLMs) learn strong statistical regularities during training, which can make them fail to properly respond to visual evidence

tutorialsarxiv-cs-cv

14 Oct 2026

JustOPD: On-Policy Distillation from Autoregressive to Diffusion Language Models

arXiv:2610.17397v1 Announce Type: new Abstract: On-policy distillation (OPD) is a post-training approach for large language models (LLMs) that enables a student model to learn a teacher model's distri

safetyarxiv-cs-lg

Language2Drive: Do Vision-Language-Action Models Really Follow the Instructions in Autonomous Driving?

arXiv:2610.16634v1 Announce Type: cross Abstract: Recent Vision-Language-Action (VLA) models increasingly use natural-language instructions to condition autonomous driving behavior. Yet existing close

MARS: Systematic Multi-Level Acceleration for World Action Models

arXiv:2610.17141v1 Announce Type: new Abstract: World Action Models (WAMs) have emerged as a promising alternative for embodied intelligence by jointly predicting future world states and robot actions

safetyarxiv-cs-cv

Recurrent In-Context Learning for Tabular Foundation Models

arXiv:2610.14998v1 Announce Type: new Abstract: Tabular foundation models adapt to new datasets through in-context learning (ICL), and, like most transformers, they tie computational depth to the numb

SP^2ec: Adaptive Self-Speculative Decoding for Vision-Language Models

arXiv:2610.18735v1 Announce Type: new Abstract: Speculative Decoding (SD) has demonstrated its efficacy in accelerating large language model inference, but for Vision-Language Models (VLMs), the diver

Agents

Think Before You Speak: Enabling Training-Free Latent Communication Between Language Models

arXiv:2610.16165v1 Announce Type: cross Abstract: Large language models (LLMs) have demonstrated remarkable capabilities in solving complex tasks in coding, mathematical logic, and iterative reasoning

agentsarxiv-cs-lg

Applications

1M-token, multimodal decision models are here! But there is more to this one. You can classify, extract, and summarize with 1M tokens of tex…

1M-token, multimodal decision models are here! But there is more to this one. You can classify, extract, and summarize with 1M tokens of text and image input. ScaleDown's Constrained Decoding Models r

applicationsdair-ai--x

13 Oct 2026

I built a pytorch library of pretrained models for 3D point clouds following timm standards [P]

model-releasesr-machinelearning

https://preview.redd.it/m5e9anluo8vh1.png?width=1080&format=png&auto=webp&s=4c80687e6fe40036843a97ed8975ce46eaab0662 I am excited to share a project I have been working on during the past few years du

13 Oct 2026

An Input-Dependent Readout Phase for Resonant Sequence Models

arXiv:2610.12496v1 Announce Type: cross Abstract: Sequence models with a fixed-size state avoid the quadratic cost of attention, but face a design choice. An input-dependent state transition gives con

GIST: Generator-state-Informed Supervision for Tabular Foundation Models

arXiv:2610.12904v1 Announce Type: new Abstract: Tabular foundation models (TFMs) based on prior-data fitted networks typically use sampled hard query labels, leaving avoidable sampling variability in

OGPO: Offline Goal-conditioned Policy Optimization for Recoverable Vision-Language-Action Models

arXiv:2610.12914v1 Announce Type: new Abstract: Vision-language-action (VLA) models have shown strong promise in robotic manipulation, yet their post-training still predominantly relies on trajectory-

On the Encoding of Calendar Features in Covariate-Informed Time Series Foundation Models

arXiv:2610.13676v1 Announce Type: new Abstract: Time series foundation models (TSFMs) increasingly offer covariate support, with calendar information being the most common type of categorical covariat

People Making Conversation: Evaluating How Naturally Speech Models Converse

arXiv:2610.12802v1 Announce Type: new Abstract: A conversational speech model has to decide, at every pause, whether to speak. Existing evaluations test boundary detection, policy adherence, or aggreg

RSI-Anything: Unlocking Recursive Self-Improvement with World Models

arXiv:2610.13912v1 Announce Type: new Abstract: Recursive self-improvement (RSI) aims to transform interaction experience into persistent improvements, yet external feedback is costly and world-model

safetyarxiv-cs-cl

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

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

model-releasescristobal-valenzuela--x

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

10 Oct 2026

Cross-Embodiment Robot Foundation World Models with Latent Actions

model-releasesarxiv-cs-ro

arXiv:2610.10846v1 Announce Type: new Abstract: The diversity of robot embodiments and action spaces makes it challenging to build robot world models that generalize across different embodiments. We i

Enabling Preference-driven Unlearning in Few-step Distilled Text-to-Image Diffusion Models

arXiv:2610.10859v1 Announce Type: new Abstract: Text-to-image diffusion models are increasingly distilled into few-step variants and being deployed to enable fast inference. However, their ability to

safetyarxiv-cs-cv

Local Ai

I made a Mac app that uses your Ollama models to answer questions from your own folders, with the exact sentence cited

Disclosure: I'm the developer. The app is called Citenook. I wanted to ask questions across a few hundred PDFs and notes with Ollama, but every setup I tried either needed a lot of glue code or gave a

local-air-ollama

Recurrent Self-Improvement: Dynamic Cross-Loop On-Policy Distillation for Looped Language Models

arXiv:2610.10623v1 Announce Type: cross Abstract: Looped Language Models (LoopLMs) offer a parameter efficient approach to scaling reasoning by reusing shared parameters across recurrent computation s

Safe Actions Alone Do Not Ensure Safe Agents: Identifying Unfulfilled Obligations with Guard Models

arXiv:2610.11773v1 Announce Type: new Abstract: Guard models are increasingly used to safeguard LLM-based agents, primarily by identifying actions that agents are forbidden to perform. However, identi

Hardware

Super interesting NVIDIA paper on choosing base models for coding agents. It's actually a clever way to rank base checkpoints by how well ea…

Super interesting NVIDIA paper on choosing base models for coding agents. It's actually a clever way to rank base checkpoints by how well each one is likely to do as a coding agent after post-training

hardwaredair-ai--x

Applications

Towards Scalable Meta-Learning of near-optimal Interpretable Models via Synthetic Model Generations

arXiv:2511.04000v2 Announce Type: replace-cross Abstract: Decision trees are widely used in high-stakes fields like finance and healthcare due to their interpretability. This work introduces an effici

applicationsarxiv-cs-ai

TypedBench: A Benchmark for Calibration, Framing Sensitivity, and Cost in System One Decision Models

arXiv:2610.11392v1 Announce Type: new Abstract: System One models output calibrated probabilities over typed answers such as categorical choices, ordinal levels, or binary outcomes, via a non-generati

Local Ai

Anaximander: Interactively Running Geospatial Deep Learning Models on Any Compute Backend

arXiv:2610.09085v1 Announce Type: new Abstract: Applying deep learning models to satellite imagery from within geographic information systems (GIS) remains high-friction for remote sensing practitione

local-aiarxiv-cs-cv

Huge release from @odysseyml. Odyssey-3 Pro sets a new top score on Physics-IQ Verified, a benchmark that asks models to continue videos of …

Huge release from @odysseyml. Odyssey-3 Pro sets a new top score on Physics-IQ Verified, a benchmark that asks models to continue videos of real physics experiments. The robotics results stood out to

model-releasesdair-ai--x

Tutorials

Mechanics of Long-Context Hybrid Models Part 1.1: From Hybrid Attention to Hybrid Position

arXiv:2610.10114v1 Announce Type: new Abstract: The architectural design of Large Language Models (LLMs) is shifting from traditional full-attention-only models to hybrid models, which combine differe

tutorialsarxiv-cs-cl

Agents

OpenDocRouter is basically OpenRouter for document OCR You can compare and use all your favorite OCR models under a single API / billing int…

OpenDocRouter is basically OpenRouter for document OCR You can compare and use all your favorite OCR models under a single API / billing interface. They range from some of the lightweight/OSS models (

agentsjerry-liu--x

Reasoning-Token Spikes Under Prompted Untruthful Responding in Large Language Models

arXiv:2610.10405v1 Announce Type: cross Abstract: Monitoring the chain-of-thought of reasoning artificial intelligence (AI) models remains a key approach to detecting deception and other forms of misb

researcharxiv-cs-cl

A Validated Dataset and Benchmark for Coherent Multi-Diagram SysML Models

arXiv:2610.07356v1 Announce Type: cross Abstract: Systems engineers use several diagrams to describe the structure and behavior of systems. Engineers create these diagrams together to make sure that t

Are Language Models Script-Aware?

arXiv:2610.08037v1 Announce Type: new Abstract: Language models frequently generate outputs in unintended languages or scripts, a phenomenon known as off-target generation. While existing research has

researcharxiv-cs-cl

Beyond Training from Scratch: Foundation Models for Data-Efficient and Generalizable Cardiac MRI Reconstruction

arXiv:2610.08109v1 Announce Type: new Abstract: Cardiac magnetic resonance imaging reconstruction aims to recover high-quality images from undersampled acquisitions, enabling faster scans while preser

CrystalJev: thinking fast and slow with atomistic foundation models for materials discovery

arXiv:2610.06985v1 Announce Type: cross Abstract: Atomistic foundation models triage millions of hypothetical materials but are used as slow simulators, their thresholded energies taken at face value.

researcharxiv-cs-ai

CtrlCache: Accelerating Interactive Video World Models with Control-Aware Caching

arXiv:2610.08777v1 Announce Type: new Abstract: Interactive video world models need to generate each video chunk efficiently while responding faithfully to user controls. Many systems use chunk-wise a

safetyarxiv-cs-cv

GeoPID: Decomposing and Steering Visual Information in Vision-Language Models

arXiv:2610.08401v1 Announce Type: cross Abstract: While recent vision-language models (VLMs) have shown outstanding performance across diverse applications, they tend to under-use visual information a

Quantifying the Gap between Understanding and Generation within Unified Multimodal Models

arXiv:2602.02140v2 Announce Type: replace Abstract: Recent advances in unified multimodal models (UMM) have demonstrated remarkable progress in both understanding and generation tasks. However, whethe

Tracking Is Not Permanence: What Video World Models Keep of a Hidden Object

arXiv:2610.07355v1 Announce Type: cross Abstract: Video world models track objects they can see; we ask what they keep of objects they cannot. We hide an object from a frozen V-JEPA 2 predictor and co

Transferable Spatial Temporal Coherence Adversarial Attack on Black-Box Vision Language Models for Autonomous Driving

arXiv:2610.08331v1 Announce Type: cross Abstract: The rapid integration of Vision Language Models (VLMs) into sensitive systems introduces critical safety vulnerabilities that remain unexplored in exi

safetyarxiv-cs-ai

Unsupervised Long-Tailed Adaptation of Vision-Language Models

arXiv:2610.07903v1 Announce Type: new Abstract: Adapting vision-language models to downstream tasks has achieved remarkable success by leveraging pseudo-labels generated from unlabeled data. Existing

Benchmarking Generative Trajectory Models for Active-Inference Control

model-releasesarxiv-cs-ro

arXiv:2610.05692v1 Announce Type: new Abstract: Learning from trajectory demonstrations offers a route to active-inference control of complex systems whose dynamics are difficult to model explicitly.

Construction and Evaluation of Machine Learning Models for Near-Real-Time Fire Detection from MTG FCI Imagery

arXiv:2610.05154v1 Announce Type: new Abstract: Geostationary satellite observations are important for wildfire detection and monitoring. The current study evaluates machine learning models for MTG FC

researcharxiv-cs-cv

Do Small Language Models Learn to Negotiate? A Controlled Scaling Study of RL-Trained Sellers

arXiv:2610.06204v1 Announce Type: cross Abstract: LLM agents are starting to own the full customer experience. Soon, LLMs may be selling and buying on behalf of companies and customers respectively. S

EgoExo-Next:Benchmarking Vision-Language Models on Visual-Option Next-State and Cross-View Reasoning

arXiv:2610.04506v1 Announce Type: new Abstract: Vision-language models (VLMs) are increasingly evaluated for egocentric and cross-view video reasoning, yet existing benchmarks largely focus on semanti

EpicWorldModel: Exploration-driven Planning with Latent World Models

arXiv:2610.05996v1 Announce Type: new Abstract: Latent world models based on Joint-Embedding Predictive Architecture (JEPA) are deterministic by design. While successful in fully observable scenarios,

Local Ai

Generative World Models Enable Predictive Control of Laser Melt Pool Dynamics

arXiv:2610.06250v1 Announce Type: new Abstract: World models, which learn how environments respond to actions, are emerging as a powerful paradigm for planning through imagined futures, transforming d

local-aiarxiv-cs-lg

Gradient-Free Sampling from Generative Models via Stochastic Bounded Extremum Seeking

arXiv:2610.04568v1 Announce Type: cross Abstract: We introduce a sampling approach for energy- and score-based generative models that requires no gradient evaluations of the model. Replacing the drift