Search: “models”

PhySimCode: A Benchmark and Evaluation Method for Physics Video to Code Generation

model-releasesarxiv-cs-cv

arXiv:2610.15722v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) are good at video understanding and code generation, but it remains unclear whether they can recover the physic

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SEAR: Self-Evolving Agentic Robotics

DGX agent

arXiv:2610.18792v1 Announce Type: new Abstract: Frontier language-model agents can now improve robots on their own: they write control code, test it, and keep what works as skills and memories for the

model-releasesarxiv-cs-ro

14 Oct 2026

SLEM: Spectrum-Aware Latent Expert Merging

arXiv:2610.16484v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) models scale model capacity efficiently by activating only a small subset of experts for each input, while still requiring all

Temporal Diffusion Bridge Model for Vessel Extraction Using Physics-informed Synthetic Data

arXiv:2610.14105v1 Announce Type: cross Abstract: Accurate artery extraction from X-ray coronary angiography (XCA) is essential for coronary artery disease diagnosis and intervention. However, low ves

researcharxiv-cs-cv

TraceSampler: Making Sampling Errors Predictable and Correctable for Accelerated Generative Sampling

arXiv:2610.14332v1 Announce Type: new Abstract: Accurate sampling from continuous-time generative models can require many model evaluations. Low-step sampling reduces cost, but coarse updates introduc

researcharxiv-cs-cv

VLCQ: Post-training quantization for deep neural networks using variable length coding

arXiv:2610.15092v1 Announce Type: new Abstract: Quantization plays a crucial role in efficiently deploying deep learning models on resource-constrained devices. Post-training quantization does not req

researcharxiv-cs-cv

Agents

When Does Opponent Modeling Pay Off? Spatial Inference Stabilises Reinforcement Learning under Partial Observability

arXiv:2610.18229v1 Announce Type: cross Abstract: Deep reinforcement learning agents in partially observable competitive games must act on beliefs about an unseen opponent's intent. We study a spatial

agentsarxiv-cs-lg

WildTrace: Evaluating Training Data Detection in Realistic Large-Scale LLM Post-Training

arXiv:2610.16152v1 Announce Type: new Abstract: Although post-training significantly enhances model performance, the use of massive undisclosed data raises concerns about benchmark contamination and c

WIRE: Weight Space Implicit Representation Encoding of Frozen Video LLMs

model-releasesarxiv-cs-cv

arXiv:2610.17355v1 Announce Type: new Abstract: Video language models represent a video as a long sequence of visual embeddings in a decoder's input. Every visual embedding is processed by every decod

ZOIF: Zeroth-Order Influence Function Estimation for LLM Data Selection Using Only Forward Passes

arXiv:2610.15336v1 Announce Type: new Abstract: Influence functions enable principled data selection for large language models (e.g., identifying influential training samples for model editing, debugg

LiquidAI/LFM2.5-24B-A2B

model-releasesr-localllama

Gguf's: https://huggingface.co/LiquidAI/LFM2.5-24B-A2B-GGUF Free Demo: https://playground.liquid.ai 'LFM2.5-24B-A2B is a 24B-parameter reasoning model with only 2B active parameters, built for fast, p

13 Oct 2026

Behind-the-Meter Photovoltaic Visibility from Net Smart Meters: Deployment Regimes and Operational Insights

arXiv:2610.12527v1 Announce Type: new Abstract: Distribution operators need visibility of behind-the-meter photovoltaic (PV) generation, yet most residential customers are observed only through net sm

CoBe: A Benchmark For Conversational Counterfactual Text Editing

arXiv:2610.13057v1 Announce Type: cross Abstract: Counterfactual text editing is the ability to revise a given text in light of a hypothetical change while preserving facts not causally affected by th

FORTE: A Production Framework for Feature Evaluation and Deprecation in Industrial Recommender Systems

arXiv:2610.13806v1 Announce Type: cross Abstract: Production recommender systems have feature-lifecycle asymmetry: adding new features must produce gains on some metric, while feature removal must not

Humanize Olympiad Agents: A Multi-Session Workflow for Olympiad Problem Solving with Solve, Review, Wiki, Verify

arXiv:2610.13632v1 Announce Type: new Abstract: Large language model (LLM) agents are rapidly improving on long-horizon scientific and olympiad tasks. Recent systems have produced a Lean-formalized re

MS-GLA: Multi-Scale Gated Linear Attention for Addressing Representational Bottlenecks via Multi-Temporal Resolution

arXiv:2609.35664v2 Announce Type: replace-cross Abstract: Gated Linear Attention (GLA) Transformers advance linear recurrent models through data-dependent gating, but face a core limitation: the fixed

perturber: A Stateless Service for Semantics-Preserving Text Perturbations

model-releasesarxiv-cs-cl

arXiv:2610.12667v1 Announce Type: new Abstract: Large language model (LLM) evaluations on clean benchmarks overstate model robustness: real inputs arrive perturbed, and these meaning-preserving varian

QLoRA on ExLlamaV3 Quants - Train @ 2-8bpw

model-releasesr-localllama

EXL3-QLoRA I've built this over the last few months and I think it's stable enough to share now. A fork of ExLlamaV3, this is a native ExLlamaV3 training implementation with plain PyTorch, without tra

Qwen 3.8 Flash Next Q3 S - Benchmark creation

model-releasesr-localllama

After running a benchmark test on Exo in Opencode and being amazed by the result, I thought I'd try other models on Opencode. Many were surprisingly terrible. Especially some mid level models. Earlier

I tried three ways of getting Gemma and Qwen to update a notes file in Ollama

I ran a small test for Dory to see whether a local model could update one fact in a synthetic notes file without losing any of the others. I asked Gemma and Qwen to rewrite the file, return a patch, o

model-releasesr-ollama

10 Oct 2026

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

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

Local Ai

AtomWorld-Mirror: Macro-Step World Modeling of Critical Evolution Backbones for Materials Dynamics

arXiv:2610.11527v1 Announce Type: new Abstract: Atomistic simulation is a fundamental tool for studying long-term materials evolution, from diffusion and defect dynamics to interfacial reactions and f

local-aiarxiv-cs-ai

Brain foundation model-guided source-selective domain adaptation for cross-subject EEG decoding

arXiv:2507.21037v3 Announce Type: replace Abstract: Cross-subject motor-imagery electroencephalography (MI-EEG) decoding remains challenging because substantial inter-subject variability can cause bot

safetyarxiv-cs-lg

Emergent Inverse-Depth Scaling From Nonlinearity In Attention

arXiv:2610.11063v1 Announce Type: cross Abstract: Scaling laws describe power-law improvements in model performance with dataset size and parameter count, yet their underlying mechanisms are not fully

Language Modeling is Monotone Compression

arXiv:2610.11031v1 Announce Type: cross Abstract: A long-standing hypothesis in artificial intelligence and neuroscience posits that intelligence is closely related to compression: the ability to comp

researcharxiv-cs-ai

Mine Odyssey: Benchmarking Spatial Agentic Intelligence in the Wild

arXiv:2610.11328v1 Announce Type: new Abstract: Advances in foundation models are driving efforts to introduce agents to assist people in the physical world. Such agents require agentic spatial intell

Real Long-Term Memory for AI: A 50-Million-Token Window That Is Faster and Cheaper Than Recompute

arXiv:2610.10845v1 Announce Type: cross Abstract: A large language model can only use the text that fits in its context window, and it recomputes its internal key-value (KV) state for a prompt every t

Residual Modeling Closes the Regression and Generative Policy Gap in Robot Learning

arXiv:2610.12231v1 Announce Type: new Abstract: Learning from demonstration has enabled impressive robot behaviors. A common choice for policy learning is to use diffusion or flow matching (Flow-Polic

safetyarxiv-cs-ro

RiCo: Neural Simulation of Rigid-Body Interactions via Local Contact Reasoning

arXiv:2610.12333v1 Announce Type: cross Abstract: Accurate simulation of rigid-body interactions is essential for predictive physical world models. Despite recent progress in modeling object dynamics,

Searching for 'Harmful Refusal': A Psychometric Audit of an AI Safety Benchmark

arXiv:2610.12409v1 Announce Type: new Abstract: Safety benchmarks typically report one overall score for a suite of datasets, each of which may target one or more safety-related attributes, so models

Tutorials

USDCraft: Geometrically Grounded Programmatic Modeling of Articulated 3D Assets for Simulation

arXiv:2610.11322v1 Announce Type: new Abstract: Geometrically faithful and functional articulated 3D assets are essential for real-to-sim robot manipulation, where policies trained in simulation must

tutorialsarxiv-cs-ro

World-Model Policy Arbiter for Goal-Conditioned Reinforcement Learning

arXiv:2610.10932v1 Announce Type: new Abstract: Offline goal-conditioned reinforcement learning (GCRL) has produced a diverse set of goal-reaching algorithms, yet no single algorithm performs best acr

safetyarxiv-cs-lg

Constitution-Guided Watermarking

arXiv:2610.09552v1 Announce Type: cross Abstract: Watermarking enables language model providers to identify text generated by their models. However, its desired properties can conflict (ie~stronger wa

safetyarxiv-cs-cl

Agents

Controllable Crowd Generation through World-Model Planning

arXiv:2610.09438v1 Announce Type: new Abstract: Crowd simulation plays a central role in robot navigation, autonomous driving, and urban planning. For these applications, realistic simulation requires

agentsarxiv-cs-cv

Decoupling Logic from Persona: Structural Immunity of Edge LLM Agents to Context Pollution

model-releasesarxiv-cs-cl

arXiv:2610.09772v1 Announce Type: new Abstract: Small language-model agents on edge devices must hold a persona and reason correctly at once, inside one context window that fills with conversational h

Identifiability of a dissipative knowledge-dynamics model: exact recovery under designed excitation, degeneration on observational data

arXiv:2610.09889v1 Announce Type: new Abstract: Human learning is a dissipative dynamical process: mastery accumulates through practice, decays through forgetting, and propagates across interdependent

researcharxiv-cs-lg

Jevjitsu: Or, How We Tried Generalized Classifiers on Everything

Classification is one of the oldest problems in machine learning. Unlike modern decoding transformers, most classification models were non-autoregressive by nature. Before Jev, the common approaches w

model-releasesqdrant

Order-Optimal Sample Complexity of Rectified Flows

arXiv:2601.20250v2 Announce Type: replace Abstract: Recently, flow-based generative models have shown superior efficiency compared to diffusion models. In this paper, we study rectified flow models, w

researcharxiv-cs-lg

Local Ai

ProtocolMatch: Protocol-Dependent Model Selection for Scientific Dynamics Forecasting

arXiv:2610.10239v1 Announce Type: new Abstract: Scientific dynamics forecasting is often framed as an architecture choice, although deployment is also determined by observed history, rollout feedback,

local-aiarxiv-cs-lg

Agents

SPW-Nav: A Streaming Panoramic World Model for Language-Guided Navigation

arXiv:2610.08941v1 Announce Type: new Abstract: Language-guided panoramic video generation benefits various downstream applications, such as interactive 3D scene exploration, virtual reality experienc

agentsarxiv-cs-cv

Tiny-Scale Chinese BERT Pretraining: A Controlled Comparison of MLM, WWM, and MacBERT Strategies

arXiv:2610.08879v1 Announce Type: new Abstract: Pretraining strategies significantly impact the quality of language models, yet existing comparisons of Masked Language Modeling (MLM), Whole Word Maski

researcharxiv-cs-cl

Video Prediction Policy 2: Predict Better, Act Better

model-releasesarxiv-cs-cv

arXiv:2610.10270v1 Announce Type: new Abstract: World action models (WAMs) have emerged as an important class of generalist robot policies, aiming to transfer video prediction priors to action learnin

Banger paper from NVIDIA. One exciting trend I am seeing is building verifiable environments for your agents and training the harness alongs…

Banger paper from NVIDIA. One exciting trend I am seeing is building verifiable environments for your agents and training the harness alongside the model. Co-evolving the harness and the model is a bi

model-releasesdair-ai--x

Local Ai

Computationally efficient goodness-of-fit tests through kernelized Stein discrepancy

arXiv:2512.20007v3 Announce Type: replace-cross Abstract: Models with intractable normalizing constants are widely used in statistics and machine learning. Assessing the adequacy of such models poses

local-aiarxiv-cs-lg

Disentangling Paradigm, Identifier, and Decoding in Generative Retrieval

arXiv:2610.08716v1 Announce Type: cross Abstract: Generative retrieval trains a language model to generate the identifier of a relevant document. Recent work replaces the autoregressive decoder with d

researcharxiv-cs-cl

Hardware

Feature Space Analysis by Guided Diffusion Model

arXiv:2509.07936v3 Announce Type: replace Abstract: This paper aims to analyse the feature space of a vision-related Deep Neural Network (DNN) by proposing a decoder that can generate an image whose f

hardwarearxiv-cs-cv

FlowCF: Sparse Counterfactual Explanations for Mixed-Type Tabular Data using Flow Matching

arXiv:2610.08537v1 Announce Type: cross Abstract: In the field of Explainable AI (XAI), counterfactual (CF) explanations interpret a model's decision by suggesting the changes to the input that would