Search: “models”

RefAM: Attention Magnets for Zero-Shot Referral Segmentation

arXiv:2509.22650v3 Announce Type: replace Abstract: Most existing approaches to referring segmentation achieve strong performance only through fine-tuning or by composing multiple pre-trained models,

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RESIST: Resilient Decentralized Learning Using Consensus Gradient Descent

DGX agent

arXiv:2502.07977v3 Announce Type: replace Abstract: Empirical risk minimization (ERM) is a cornerstone of modern machine learning. This paper focuses on the man-in-the-middle (MITM) attack, wherein ad

model-releasesarxiv-cs-lg

22 Sept 2026

Resolution-Flexible Decoding for Hybrid Neural Video Representations

arXiv:2609.23555v1 Announce Type: cross Abstract: Neural video representations (NVRs) represent videos using neural network parameters and, in hybrid formulations, frame-wise latent embeddings. Althou

Revisiting Multi-View Stereo: A Sequence-to-Sequence Formulation

arXiv:2609.24850v1 Announce Type: new Abstract: Computing accurate geometry from multi-view images is a fundamental problem in computer vision. Recent feed-forward (FF) models jointly estimate 3D geom

RiverVLN: Phase-Grounded Temporal Vision--Language Navigation for Unmanned Surface Vehicles

arXiv:2609.23423v1 Announce Type: new Abstract: Vision-language navigation (VLN) has largely been developed for indoor and terrestrial robots, where language can often be treated as a static goal and

Robust Market Making with Hawkes Order Flow and Price Impact via Adversarial Reinforcement Learning

arXiv:2609.22785v1 Announce Type: new Abstract: Market-making strategies in real limit order book markets face substantial model uncertainty and regime-shift risk. Existing adversarial reinforcement l

safetyarxiv-cs-lg

RopeFormer: Cross-Trial Adaptation from Interaction History for Dynamic Rope Manipulation

arXiv:2609.23432v1 Announce Type: new Abstract: Dynamic rope manipulation is highly sensitive to unknown object dynamics: the same robot motion can produce substantially different responses across rop

SafeTune: A Unified Faithful Library for Auditing and Repairing Safety Drift in Fine-Tuned LLMs

arXiv:2609.22153v1 Announce Type: new Abstract: Methods for addressing safety drift in fine-tuned Large Language Models (LLMs) are scattered across incompatible implementations, lifecycle stages, and

safetyarxiv-cs-lg

Local Ai

SAGE: Optimal-Stopping Peer Selection for Decentralised Federated Learning

arXiv:2609.23773v1 Announce Type: cross Abstract: Decentralised federated learning replaces server aggregation with peer-to-peer model exchange, making collaborator selection a local decision under un

local-aiarxiv-cs-lg

Local Ai

ServerlessLoRA: Enabling Low-Latency Serverless Multi-LoRA Serving

arXiv:2505.14468v2 Announce Type: replace Abstract: Multi-LoRA (Low-Rank Adaptation) serving allows many specialized LLM variants to share the same base model by attaching lightweight adapters. This m

local-aiarxiv-cs-lg

SewFusion: Tailored Generation of Topology and Panel-Level Geometry for Sewing Patterns

arXiv:2609.23548v1 Announce Type: new Abstract: Generating sewing patterns from images and text requires modeling a heterogeneous representation composed of discrete topology and continuous geometry.

SG-FSM: A Self-Guiding Zero-Shot Prompting Paradigm for Multi-Hop Question Answering Based on Finite State Machine

arXiv:2410.17021v2 Announce Type: replace Abstract: Large Language Models with chain-of-thought prompting, such as OpenAI-o1, have shown impressive capabilities in natural language inference tasks. Ho

Signal-Informed Temporal Routing for Vinyl Defect Regime Detection

arXiv:2609.23164v1 Announce Type: cross Abstract: Vinyl restoration systems must distinguish isolated clicks, short bursts, dense crackle, and overlapping damage before selecting a repair operation. W

SmallSatSim: A GPU-Accelerated Microgravity Robotics Toolkit for Planning, Control, and Policy Learning

arXiv:2603.14598v2 Announce Type: replace Abstract: Microgravity rendezvous and close proximity operations (RPO) is a growing area of interest for applications spanning in-space assembly and manufactu

safetyarxiv-cs-ro

SolarFlowRefiner: Refinement-Aware Flow Matching for Surface Solar Radiation Downscaling

arXiv:2609.22126v1 Announce Type: cross Abstract: High-resolution surface solar radiation (SSR) is important for solar forecasting and grid operation. However, physically consistent reanalysis product

Speech-to-SOAP: End-to-End Summarization of Medical Dialogues: KIT@BeTraC 2026

arXiv:2608.24327v2 Announce Type: replace Abstract: With the advent of Large Language Models and its instruction following capabilities a promising application is the task of summarization. Within thi

Applications

SRPR-Net: Semantic and Relational Prompt Refinement for Automated SAM-based Instance Segmentation

arXiv:2609.24226v1 Announce Type: new Abstract: Instance segmentation is a fundamental computer vision task with diverse real-world applications. Recently, prompt-driven foundation models have shown p

applicationsarxiv-cs-cv

STA-TFM: Spatio-Temporal Aggregation Across Views TransForMer for Pose Estimation

arXiv:2609.24482v1 Announce Type: new Abstract: Monocular 3D human pose estimation (HPE) remains challenging due to depth ambiguity, occlu- sions, and the need for temporal consistency. While multi-vi

STAR: Scene- and Task-Aware 4D Radar Preprocessing Towards End-to-End Cognitive Radar

arXiv:2609.24151v1 Announce Type: new Abstract: Four-dimensional (4D) Radar has emerged as a key sensor for environmental perception, providing range, azimuth, elevation, and Doppler measurements whil

Statistical Inference for Adversarial Training: Central Limit Theorems via Optimal Transport

arXiv:2609.22240v1 Announce Type: new Abstract: The purpose of this paper is to rigorously quantify the statistical and learning-theoretic properties of adversarial training models for classification.

researcharxiv-cs-lg

Streaming Deep Reinforcement Learning Finally Works

arXiv:2410.14606v3 Announce Type: replace Abstract: Learning from a stream of experience as it arrives, also known as streaming learning, is a core part of natural learning. However, reliable streamin

Structure Before Sampling: Community-Aware Core-Set Selection for Data-Efficient Text-to-Speech

arXiv:2609.24275v1 Announce Type: new Abstract: Text-to-speech (TTS) corpora are costly to record, yet many utterances add little new phonetic information. Core-set selection reduces this cost by choo

Subgoal Search For Complex Reasoning Tasks

arXiv:2108.11204v4 Announce Type: replace-cross Abstract: Humans excel in solving complex reasoning tasks through a mental process of moving from one idea to a related one. Inspired by this, we propos

Local Ai

Tail-Weight Control and Localized Generalization in Nearly Low-Rank Adversarial Classification

arXiv:2609.23688v1 Announce Type: new Abstract: We study norm-constrained linear classification under Eu clidean adversarial perturbations in a Gaussian model with a low-dimen sional informative subsp

local-aiarxiv-cs-lg

Teacher Should Think Ahead: Adaptive Continuations for Reliable On-Policy Distillation

arXiv:2609.22254v1 Announce Type: new Abstract: On-policy distillation (OPD) is a promising approach for transferring knowledge between language models, where a student receives dense token-level supe

safetyarxiv-cs-lg

The Price of Self-Calibration: Exact Evidence Budgets and Manufactured Blind Sets in Adaptive Monitoring

arXiv:2609.23254v1 Announce Type: new Abstract: Self-calibrating monitors adapt their threshold online to guarantee a prescribed long-run false-alarm rate under arbitrary drift. We compute the price o

Tutorials

The Undetected Damage of Quantization on Retrieval and How to Fix It

arXiv:2609.24322v1 Announce Type: new Abstract: We show that a quantized model that keeps its classification accuracy still changes 14 to 46% of its top-1 retrieval results, and that aggregate ranking

tutorialsarxiv-cs-lg

Token Utility Is Selection-Conditioned: Coupled Selection of Prompt Context and Response Supervision for Efficient Instruction Tuning

arXiv:2609.22943v1 Announce Type: new Abstract: Efficient large language model (LLM) instruction tuning requires selecting response supervision with supporting prompt context. Existing methods typical

researcharxiv-cs-lg

Toollery: Scaling LLM Agents to Thousands of Skills and Tools

model-releasesarxiv-cs-cl

arXiv:2609.22218v1 Announce Type: cross Abstract: As LLM agents are exposed to hundreds to tens of thousands of skills, tools, and API functions, full-library prompting becomes costly, slow, and less

Agents

Towards Full Pipeline FP8 Reinforcement Learning for LLMs

arXiv:2609.22870v1 Announce Type: new Abstract: Reinforcement learning (RL) has become a key technique for improving the reasoning and agentic abilities of large language models (LLMs). Although FP8 q

agentsarxiv-cs-lg

Training-Free Spectral Transductive Refinement for Cross-Domain Few-Shot Classification

arXiv:2609.23758v1 Announce Type: new Abstract: Few-shot recognition with frozen visual features is especially fragile under domain shift and one-shot supervision, where a single labelled image is an

Triggers and Diagnostics for LLM-Based Interpretability Failures in Active Inference Agents

arXiv:2609.23215v1 Announce Type: new Abstract: LLM explainers are increasingly attached to autonomous agents as runtime oversight, with operators reading a generated account of the agent's beliefs an

Tsallis Entropy Regularization for Linear Quadratic Regulator and Kullback-Leibler Control

arXiv:2403.01805v2 Announce Type: replace-cross Abstract: Shannon entropy regularization is widely adopted in optimal control due to its ability to promote exploration and enhance robustness, e.g., ma

Type-Driven Tokenization for Brahmic Scripts

arXiv:2609.22125v1 Announce Type: new Abstract: Standard tokenizers used in large language models produce malformed text when applied to Brahmic scripts. They are a family of abugidas, writing systems

VibeMemBench: Evaluating Memory Systems for Coding Agents on Real Repository Coding Tasks

model-releasesarxiv-cs-cl

arXiv:2609.23570v1 Announce Type: cross Abstract: Coding agents operate on real repository coding tasks, and persistent memory systems promise to reuse experience across tasks. Yet existing evaluation

Video-based Surgical Skill Assessment Using Dynamics-and-Uncertainty-Aware Tree-based Gaussian Process Classifier

arXiv:2609.24619v1 Announce Type: new Abstract: The proposed pipeline integrates a representation-flow convolutional neural network with a dynamics- and uncertainty-aware tree-based Gaussian Process c

Vision Transformers versus convolutional neural networks for fine-grained orchid genus identification in a species-rich, data-poor flora: a controlled benchmark on the Orchidaceae of New Guinea

arXiv:2609.24064v1 Announce Type: new Abstract: New Guinea is the world's richest island flora (~2,856 orchid species), yet most species are represented by only a handful of photographs, far fewer tha

Tutorials

VividCam: Learning Unconventional Camera Motions from Virtual Synthetic Videos

arXiv:2510.24904v2 Announce Type: replace Abstract: Although recent video generative models are getting more capable of following external camera controls, imposed by either text descriptions or camer

tutorialsarxiv-cs-cv

VOLTA: Improving Generative Diversity by Variational Mutual Information Maximizing Autoencoder

arXiv:2307.00852v3 Announce Type: replace Abstract: The natural language generation domain has witnessed great success thanks to Transformer models. Although they have achieved state-of-the-art genera

Want Better Synthetic Data? Steer It: Activation Steering for Low-Resource Language Generation

arXiv:2606.18389v2 Announce Type: replace Abstract: Large language models (LLMs) have become an effective tool for synthetic data generation, including for low-resource languages, where generated data

What Makes a Good Medical Image Tokenizer? Rethinking Reconstruction and Generation in Medical Image Tokenization

arXiv:2609.24691v1 Announce Type: new Abstract: Latent diffusion models now dominate medical image generation, and every such pipeline rests on a tokenizer that compresses images into the latent codes

When Does Adversarial Refinement Help? A Negative Result and Open Problem in Adapting R3GAN to Time Series Imputation

arXiv:2609.23102v1 Announce Type: new Abstract: Diffusion models and transformers have supplanted GANs for multivariate time series imputation, largely on grounds of GAN training instability. R3GAN (N

researcharxiv-cs-lg

When Does Touch Matter? Charting the Vision-Interaction Gap in Cluttered Dexterous Grasping

arXiv:2609.24068v1 Announce Type: new Abstract: Dexterous grasping in clutter poses a basic sensing question: when do tactile measurements and external wrench estimates improve on visual geometry? Occ

Zeva-Ego: Egocentric Mid-Training with In-Context Causal Learning for Robot Manipulation

arXiv:2609.24411v1 Announce Type: new Abstract: Egocentric video offers a scalable source of physical interaction experience, yet translating it into robot-executable knowledge and enabling continual

A Training-Free Proactive Defense Against Partial Speech Manipulation via Self-Embedding Steganography

model-releasesarxiv-cs-ai

arXiv:2608.25285v2 Announce Type: replace-cross Abstract: Partial deepfake speech, where only limited segments of an utterance are synthesized or manipulated, poses a significant challenge to existing

AeRove: A Compact Bimodal Aerial-Terrestrial Drone with Rapid Bistable Reconfiguration for Close-Range Pipeline Inspection

arXiv:2609.20965v1 Announce Type: new Abstract: Close-proximity pipeline inspection is challenging for standard drones due to high hovering power consumption, airflow sensitivity, and propeller wash i

Aligning with Lived Experience: Heterogeneous Benefits of Fine Tuning in Mental Health Support Generation

arXiv:2609.21075v1 Announce Type: cross Abstract: As access to professional mental healthcare remains limited, many individuals turn to online platforms such as Reddit to seek peer support situated wi

safetyarxiv-cs-ai

Attention-Aware Routing: Coupling Routing and Attention in MoEs

arXiv:2609.20974v1 Announce Type: new Abstract: In Mixture-of-Experts language models, the router typically selects and weights experts based on the token's hidden state, utilizing limited contextual

researcharxiv-cs-ai