Search: “models”

Learning via Self-Consistency for Diffusion-based Video Reasoning

arXiv:2609.36826v1 Announce Type: new Abstract: Video generation models have demonstrated emerging zero-shot capabilities for visual reasoning, perception, and other vision tasks. However, diffusion-b

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LOCO-AdaMP: Built-in LOCO Inference for Adaptive Minipatch Ensembles with Enhanced Prediction

DGX agent

arXiv:2609.36396v1 Announce Type: cross Abstract: As black-box machine learning models become increasingly common, extracting interpretations with uncertainty quantification has become a critical chal

researcharxiv-cs-lg

30 Sept 2026

LongCat-DeepResearch Technical Report

arXiv:2609.36071v1 Announce Type: new Abstract: We present LongCat-DeepResearch, a deep research system that combines an enhanced LongCat model with a multi-agent workflow for producing comprehensive,

Looped Transformers as Optimizers

arXiv:2609.37379v1 Announce Type: new Abstract: Looped Transformers provide a parameter-efficient approach to depth scaling by repeatedly applying shared Transformer blocks. Recent reasoning models ha

LoopICL: Looping a single transformer block to solve tabular tasks

arXiv:2609.36108v1 Announce Type: cross Abstract: Tabular foundation models using in-context learning have recently surpassed gradient-boosted trees on predictive tabular tasks. However, recent mechan

Making Analog Training Scale: Co-Designing Mapping, Optimizer, and Converters

arXiv:2609.36584v1 Announce Type: new Abstract: Analog in-memory computing (AIMC) offers an alternative for model training by executing matrix operations directly where weights are stored. However, sc

MCPTox: A Benchmark for Tool Poisoning Attack on Real-World MCP Servers

arXiv:2508.14925v2 Announce Type: replace-cross Abstract: By providing a standardized interface for LLM agents to interact with external tools, the Model Context Protocol (MCP) is quickly becoming a c

Med-RADIO: Reducing All Medical Domains Into One via Multi-Teacher Distillation

arXiv:2609.37682v1 Announce Type: new Abstract: The rapid expansion of large-scale medical datasets and computational resources has driven significant progress in medical foundation models. Given the

Mnemon: Raw Records, Fast Judgments, Slow Thoughts

arXiv:2609.36059v1 Announce Type: cross Abstract: Long-term memory lets an LLM assistant use a history it can no longer reread, and most memory systems build it by rewriting conversations into facts,

Tutorials

Neural networks for spectral optimization

arXiv:2609.36047v1 Announce Type: cross Abstract: Given a functional dependent on the spectrum of a differential operator, we address the problem of finding a domain which optimizes this functional. P

tutorialsarxiv-cs-ai

Nonpreemptive Scheduling While Learning Context-Dependent Service Rates

arXiv:2609.37660v1 Announce Type: new Abstract: We study nonpreemptive contextual queueing bandits in a single-server system. Each job is represented by a d-dimensional context vector; in each round,

OmniVCBench: Benchmarking Evidence-Grounded Multimodal Reasoning Towards AI Virtual Cells

arXiv:2609.37773v1 Announce Type: new Abstract: Artificial Intelligence Virtual Cells (AIVCs) are envisioned as scientific agents that simulate cellular responses, explain underlying mechanisms, and s

PACT: Pairwise-Anchored Calibrated Tuning for Single-Token Typed Decisions

arXiv:2609.35865v1 Announce Type: cross Abstract: Single-token typed-decision models answer a schema question by reading the logits of a few one-letter answer codes at a single position: they are fast

Physics-Guided Flow-Map Matching for Precipitation Nowcasting

arXiv:2609.37487v1 Announce Type: new Abstract: Precipitation nowcasting, generating future radar fields from past observations, is critical for flood warning and disaster response. It is also a deman

Safety

Population Fidelity: Evaluating Population Representativeness in LLMs

arXiv:2609.36253v1 Announce Type: cross Abstract: Large language models (LLMs) show considerable potential in simulating human attitudes and preferences. Prior work finds that LLM-generated responses

safetyarxiv-cs-ai

Procedural Core: A Compact Recurrent Initialization for Vision Transformers

arXiv:2609.37631v1 Announce Type: cross Abstract: Transformers are typically trained from random initialization, requiring all their capabilities to emerge from large-scale optimization. Recent work s

ProCTI: Prototype-Refined Global Conditioning for Diffusion-Based Time Series Imputation

arXiv:2609.37632v1 Announce Type: cross Abstract: Time series imputation has progressed from statistical and deep learning approaches to diffusion-based models, which have shown strong recent performa

Representable but Unlearned: Encoding Rank and the Interaction-Prediction Floor

arXiv:2609.36208v1 Announce Type: cross Abstract: Input encodings can restrict which measured contrasts a predictor can jointly reproduce, even when no single contrast is forced to vanish. We compute

Risk-Aware Semantic Grounding for Trustworthy LLM-Based Robot Planning

arXiv:2609.37554v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as high-level planners in robot navigation, but their outputs may become unreliable when instructio

ROSS: Relearning from Self-Generated Rollouts through Selective Supervision

arXiv:2609.35954v1 Announce Type: cross Abstract: Large language model post-training generates self-generated rollouts through reinforcement learning and on-policy distillation, yet this experience is

SEED: Self-Speculative Decoding via Implicit Encoder-Decoder

arXiv:2609.36590v1 Announce Type: new Abstract: Self-speculative decoding accelerates large language model (LLM) inference by drafting tokens from the target model itself, but faces a sharp tradeoff b

researcharxiv-cs-cl

Serverless gossip training of LSTM failure detectors: A matched-protocol comparison with federated, local and centralized learning on NASA C-MAPSS

arXiv:2609.35792v1 Announce Type: new Abstract: Industrial predictive maintenance increasingly depends on learning from equipment spread across sites whose sensor data cannot easily be pooled. Federat

SINGED: Correct Outputs Do Not Certify Safe Execution in LLM Agents

arXiv:2609.35889v1 Announce Type: cross Abstract: Tool-using language-model agents select and execute third-party artifacts. Different implementations can return the requested output while producing h

Think, Then Look: Active Spatial Reasoning for House-Scale 3D Scene Understanding

arXiv:2512.03284v2 Announce Type: replace Abstract: Spatial reasoning in large-scale 3D environments remains challenging for current vision--language models, which are typically constrained to room-sc

TopoEmbedX: A General Framework for Representation Learning on Topological Domains

arXiv:2609.37884v1 Announce Type: new Abstract: Topological structures such as simplicial complexes, hypergraphs, and cell complexes extend standard graph models by modeling higher-order relationships

researcharxiv-cs-lg

Variational Augmented Invertible Koopman Autoencoder for probabilistic time series forecasting

arXiv:2609.37435v1 Announce Type: new Abstract: Neural Koopman autoencoder models have been shown to successfully build a latent embedding with linear dynamics for arbitrary dynamical systems, enablin

researcharxiv-cs-lg

Local Ai

What Shared Prefixes Hide: Trajectory Dropout for On-Policy Distillation

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

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

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

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

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,

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

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