Search: “models”

arXiv:2609.33455v2 Announce Type: replace Abstract: On-policy distillation (OPD) trains a student model on its own trajectories using dense token-level feedback from a stronger teacher model. Since ea

local-aiarxiv-cs-ai

30 Sept 2026

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When do data mixtures improve scaling laws? Insights from high-dimensional regression

DGX agent

arXiv:2609.38011v1 Announce Type: new Abstract: Modern machine learning systems are trained on mixtures of data from different domains, and choosing the right mixture can substantially improve downstr

model-releasesarxiv-cs-lg

30 Sept 2026

A Multi-Dataset Benchmark of YOLO-Based Weed Detection in Precision Agriculture

arXiv:2609.33991v1 Announce Type: new Abstract: Weed detection is an important component of precision agriculture, enabling site-specific weed management and reducing unnecessary herbicide use. Althou

ANaLOG: Anisotropic Native-Latent Operator Guidance for Solving Inverse Problems

arXiv:2609.31933v1 Announce Type: cross Abstract: Native-latent guidance is a recent paradigm for solving inverse problems with latent diffusion models. It replaces repeated evaluations of the image-s

researcharxiv-cs-cv

Automated Lesion Segmentation of Stroke MRI Using nnU-Net: A Comprehensive External Validation Across Acute and Chronic Lesions

arXiv:2601.08701v2 Announce Type: replace-cross Abstract: Accurate and generalisable segmentation of stroke lesions from magnetic resonance imaging (MRI) is essential for advancing clinical research,

researcharxiv-cs-cv

BITS: Rethinking Fair and Comprehensive Evaluation for Irregular Time Series Forecasting

arXiv:2609.33303v1 Announce Type: new Abstract: Despite recent progress in irregular time series forecasting, the field still lacks a unified benchmark for fair and comprehensive evaluation. Existing

BOCCHI: A More Realistic and Challenging Benchmark for Local Motion Blur Detection with MSDCT-UNet

arXiv:2607.10427v2 Announce Type: replace Abstract: Local motion blur detection requires pixel-level localization of blurred regions. Existing benchmarks let models rely on gradient shortcuts that fai

BR-MPPI: Barrier-Rate Guided MPPI for Enforcing Multiple Inequality Constraints with Learned Signed Distance Fields

model-releasesarxiv-cs-ro

arXiv:2506.07325v2 Announce Type: replace Abstract: Model Predictive Path Integral (MPPI) control provides a sampling-based framework for optimal control, while Control Barrier Functions (CBFs) provid

CAR-VLA: Complexity-Aware and Risk-Adaptive Reasoning for Autonomous Driving

arXiv:2609.34387v1 Announce Type: new Abstract: Existing adaptive reasoning methods for driving Vision-Language-Action (VLA) models primarily focus on whether to reason, overlooking how reasoning shou

CoCurve: Cross-Module Co-Pruning Curvature for Structured LLM Pruning

arXiv:2607.17568v2 Announce Type: replace Abstract: Resource-constrained deployment requires sustaining large language model (LLM) capabilities as models scale under fixed memory and computation budge

researcharxiv-cs-lg

Safety

Coding Agent Memory Post-training: Unlocking the Memory Potential of Pre-trained File Operations for Long-Horizon Tasks via Reinforcement Learning

arXiv:2609.34422v1 Announce Type: new Abstract: Language-model agents increasingly tackle long-horizon tasks whose interaction histories exceed the model's active context. Recent work has begun to use

safetyarxiv-cs-lg

Cross-Dataset Generalization of Bangladeshi Rice Leaf Disease Classifiers: Benchmark, Diagnosis, and Mitigation

arXiv:2609.31709v1 Announce Type: new Abstract: Cross-dataset transfer in rice leaf disease classification remains a significant challenge, with models trained on one image collection performing subst

Applications

E-CONAN (Entailment, CONtradition And Neutral) Diagnostics Dataset Investigating Linguistic Phenomena in Arabic Natural Language Understanding

arXiv:2609.33530v1 Announce Type: cross Abstract: Natural Language Understanding (NLU) plays a crucial role in various applications, yet its performance suffers from weaknesses in handling the complex

applicationsarxiv-cs-lg

ECG-Scroll: A Long-Horizon, Streaming Benchmark and Agent Environment for Interpretation of Ambulatory Electrocardiograms

arXiv:2609.33117v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) can now interpret a standard ten-second, twelve-lead electrocardiogram (ECG) with clinically grounded, reward-v

EffiPair: Improving the Efficiency of LLM-generated Code with Differential Execution Feedback

arXiv:2604.05137v2 Announce Type: replace-cross Abstract: Large language models (LLMs) can generate functionally correct programs that differ substantially in execution efficiency. Existing inference-

Energy-aware frugal Bayesian optimization

arXiv:2609.31638v1 Announce Type: new Abstract: Modern design optimization frameworks aim first and foremost for models with the most accurate predictions without balancing computational overhead. It

Energy Vision--Language--Action: A Controlled Multimodal Benchmark for Intent-Conditioned Residential Energy Management

arXiv:2609.31648v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models are studied mainly in robotics, where visual observations and language instructions are mapped to physical actions.

EngIntervene: Benchmarking Multimodal Engineering State Understanding and Design Intervention Reasoning

arXiv:2609.33261v1 Announce Type: new Abstract: Multimodal engineering benchmarks largely evaluate static understanding, such as recognizing components, interpreting diagrams, or answering technical q

Enhancing Visual Reasoning in Chest X-Ray Report Generation Using Reinforcement Learning

arXiv:2609.31911v1 Announce Type: new Abstract: Medical report generation has made significant progress with the rise of modern vision-language models and the growing availability of large-scale medic

researcharxiv-cs-cv

ESTHER: Egocentric Stereo Hand Estimation and Reconstruction in the Wild

arXiv:2609.34817v1 Announce Type: new Abstract: Human dexterity is guided by two eyes watching two hands: binocular vision supplies the metric 3D structure that fine-grained manipulation consumes. Ego

Fast and Precise Learned Charged-Particle Trajectory Regression at the Large Hadron Collider

arXiv:2609.32479v1 Announce Type: new Abstract: We propose a training recipe that treats charged-particle trajectory parameter regression on high-energy physics detector data as a sequence-modeling ta

FedHV: Low-Overhead Hypervolume Weighting for Federated Multi-Objective Optimization

arXiv:2609.32790v1 Announce Type: new Abstract: Task-wise federated multi-objective optimization (FedMOO) trains a shared model for competing prediction objectives under heterogeneous data, partial pa

FIDAL: Diversity-Aware Federated Active Learning Under Real-World Distribution Shifts

arXiv:2609.31637v1 Announce Type: cross Abstract: Federated learning enables collaborative model training across institutions without centralizing data, yet high annotation costs, domain shifts, and c

Forecast-Necessary Causal Discovery for Nonlinear Political Panel Data: Feedback, Functional Form, and the Dynamics of Democratization

arXiv:2609.34115v1 Announce Type: cross Abstract: A non-significant coefficient in a dynamic panel model need not imply the absence of a relationship. It may instead reflect heterogeneous effects aver

researcharxiv-cs-lg

Generative AI-Based Data Augmentation for Oral Lesion Classification: The PhotoMOCI Dataset and Benchmark

arXiv:2609.35226v1 Announce Type: new Abstract: Early detection of oral cancer via photographic imaging presents a promising avenue for large-scale oral cavity screening. However, the development of r

GroupMask: Layer-Adaptive Group-wise Sparsity for Semi-Structured LLM Pruning

arXiv:2609.33977v1 Announce Type: new Abstract: Semi-structured pruning compresses large language models (LLMs) while keeping a regular sparse structure, but the prevailing N:M pattern fixes the same

HERO-MoE: Historical Expert Routing with Scale-Preserving Fusion

arXiv:2609.32581v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) architectures have become a standard way to scale model capacity while keeping computation sparse, yet routing remains a key

Inference Engines will become a series of one-offs

model-releasesr-localllama

ninfer, dwarfstar, Splash, llamAmpere, gufo, etc. We've all seen them popping up, great tok/s, people loving them. Forks of llama.cpp or another engine, or made from scratch. For better or worse, the

Learning When to Recur: Token-Adaptive Recursion for Imbalanced Ophthalmic Domain Incremental Learning

arXiv:2609.32785v1 Announce Type: cross Abstract: Domain incremental learning is essential for adapting ophthalmic deep learning models to sequential clinical domains while preserving diagnostic exper

Agents

Marathoner: Ultra-Long-Horizon Autonomous Intelligence

arXiv:2609.34378v1 Announce Type: new Abstract: Humans naturally possess the ability to work persistently toward long-term goals. Given a challenging task, humans can continuously work for months or e

agentsarxiv-cs-cv

MDL-Calibrated Significance-Gain Pair Encoding: Replication-Aware Automatic Stopping for Subword Tokenization

arXiv:2609.31705v1 Announce Type: new Abstract: Byte-Pair Encoding (BPE) constructs subword vocabularies through greedy pair merging, but conventional BPE requires the number of merges or target vocab

Muon Sublates the Edge of Stability in LLM Pretraining

arXiv:2609.34915v1 Announce Type: new Abstract: Muon is increasingly used for language-model pretraining, yet its large-step dynamics are not captured by the classical edge-of-stability (EoS) picture

Local Ai

Natural Image Autoencoder-Based fMRI Representations for Trait and State Prediction

arXiv:2609.34167v1 Announce Type: new Abstract: Foundation models pre-trained on large-scale fMRI datasets have shown strong downstream performance, but at substantial data and computation cost. To in

local-aiarxiv-cs-cv

OmniWeaving: Towards Unified Video Generation with Free-form Composition and Reasoning

arXiv:2603.24458v3 Announce Type: replace Abstract: While proprietary systems such as Seedance-2.0 have achieved remarkable success in omni-capable video generation, the academic research community la

Optimizing H-Graph Hybridization for Diffusion-Guided RRT

arXiv:2609.32897v1 Announce Type: new Abstract: Sampling-based motion planners guided by diffusion models produce high-quality trajectories in a single run, yet the stochastic diversity available at i

PalmLeaf-VQA: A Multi-Script Visual Question Answering Benchmark for Historical Palm-Leaf Manuscript Understanding Across Diverse Regions

arXiv:2609.31651v1 Announce Type: new Abstract: Historical manuscripts remain largely absent from modern vision-language benchmarks, leaving open how well multimodal large language models (MLLMs) hand

Applications

PanoVLN: Towards Effective Panoramic Vision-and-Language Navigation

arXiv:2609.34759v1 Announce Type: new Abstract: Recent vision-language models (VLMs) have advanced vision-and-language navigation (VLN), enabling models to predict navigation actions from visual obser

applicationsarxiv-cs-cv

Permutation-Equivariant Flow Matching for Alignment-Free Neural Weight Generation

arXiv:2609.32833v1 Announce Type: new Abstract: A trained neural network can be represented by a parameter vector in high dimensions. Learning distributions over these vectors enables the generation o

Physics-Attested Federated Learning: Securing Collaborative Anomaly Detection in Critical Water Infrastructure

arXiv:2609.34804v1 Announce Type: cross Abstract: Federated learning enables industrial operators to train shared intrusion detection models without disclosing proprietary operational telemetry. Howev

PlanGuard: A Guardrail for Multi-Step Plan Safety in Embodied Agents

arXiv:2609.32801v1 Announce Type: cross Abstract: Embodied task planners may produce multi-step plans whose subtask dependencies and interactions with the environment create physical risks during exec

Presence Is Not Faithfulness: Figurative Vehicle Intrusion in Text-to-Image Generation

arXiv:2609.32188v1 Announce Type: new Abstract: Text-to-image (TTI) models increasingly generate high-quality images from natural-language prompts, yet figurative language exposes a failure: a vehicle

PROACT-Agent: Progressive Runtime Oversight and Active Circuit-breaking for Real-Time Safety

arXiv:2609.34415v1 Announce Type: new Abstract: The transition from Large Language Models (LLMs) to agents shifts safety stakes from toxic text to irreversible environmental harm. While current defens

Probe to Act: Elevating Browser-Use Agent via Active Visual Probing

arXiv:2609.33646v1 Announce Type: cross Abstract: Browser-use agents require seamless alignment between structured web metadata and visual information, while preserving relevant context across long in

Agents

Prospective Interpretation Risk: Principled Communication Control Between LLMs

arXiv:2609.33885v1 Announce Type: cross Abstract: Large language model (LLM) agentic systems increasingly rely on models communicating with one another, yet existing uncertainty and multi-agent method

agentsarxiv-cs-lg

Quoting Anthropic Frontier Red Team

model-releasessimon-willison

We evaluate several models on 100 tasks from the [internal Binary Exploitation benchmark] (selected at random), and find that GLM-5.3 develops full control flow hijacks in 4% of the trials; Claude Myt

Applications

Reading Too Much into Context: Passive Exposure Can Steer LLM Decisions

arXiv:2609.33065v1 Announce Type: cross Abstract: Large language model (LLM) assistants can now search the web and consult external sources while completing user requests. These sources can provide us

applicationsarxiv-cs-lg

REALIS: A Curated Dataset for Studying the Challenges of AI Image Detection

arXiv:2609.32734v1 Announce Type: new Abstract: AI-generated image detectors are often evaluated on benchmarks where real and synthetic images differ in content, quality, or generation artifacts, allo

Recipe-Matching, Not Equivalence

arXiv:2609.31927v1 Announce Type: cross Abstract: MathNet-Retrieve asks a retriever to find, for a math problem, a document stating the same problem. An LLM under one fixed prompt writes each gold doc