Search: “models”

OOD Generalization as a Bifurcation Problem

arXiv:2609.33562v1 Announce Type: new Abstract: Systematic out-of-distribution (OOD) generation remains a critical bottleneck for continuous-time generative models. While standard joint classifier-fre

Agents

Optimal Networks for Agentic Information Aggregation

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arXiv:2609.35537v1 Announce Type: new Abstract: We study information aggregation in the networked learning model introduced by Kearns, Roth, and Ryu (SODA 2026). There is a fixed distribution over d f

agentsarxiv-cs-lg

29 Sept 2026

Tutorials

Optimal Transport Dropout for Structured Predictive Uncertainty

arXiv:2609.33377v1 Announce Type: new Abstract: Deterministic neural networks and neural operators provide point predictions with no intrinsic measure of reliability. Yet, predictive uncertainty may s

tutorialsarxiv-cs-lg

Over-the-Air Federated Learning in Heterogeneous Mobile Wireless Networks

arXiv:2609.32832v1 Announce Type: new Abstract: Over-the-air computation has emerged as a scalable and efficient solution for deploying federated learning algorithms in wireless networks by exploiting

Pay for Hints, Not Answers: LLM Shepherding for Cost-Efficient Inference

arXiv:2601.22132v2 Announce Type: replace Abstract: Large Language Models (LLMs) deliver state-of-the-art performance on complex reasoning tasks, but their inference costs limit deployment at scale. S

PI-NOMT: Physics-Informed Neural Optimal Mass Transport for Brain Fluid Dynamics

arXiv:2609.33857v1 Announce Type: new Abstract: Recovering hidden transport mechanisms from sparse spatiotemporal observations is a fundamental inverse problem in scientific machine learning. In brain

PIVOT: Pivot-Aware On Policy Self Distillation for Multi-Turn VLM Agents

arXiv:2609.35303v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) via Group-Relative Policy Optimization (GRPO) is widely used for multi-turn VLM agent training, ye

Predicting Block-Coordinate Performance via Cross-Curvature

arXiv:2609.33489v1 Announce Type: new Abstract: Simultaneous and sequential block updates are two basic optimization strategies used across machine learning, such as neural-network training, federated

Propagate, Then Sharpen: Post-Hoc Refinement of Frozen Node Classifiers

arXiv:2609.35080v1 Announce Type: new Abstract: We study post-hoc refinement of frozen node classifiers: given only the graph G and class distributions Q predicted by a frozen model, can we improve ac

Prosodic ABX: A Language-Agnostic Method for Measuring Prosodic Contrast in Speech Representations

arXiv:2604.02102v2 Announce Type: replace-cross Abstract: Speech representations from self-supervised speech models (S3Ms) are known to be sensitive to phonemic contrasts, but their sensitivity to pro

Applications

QuantForge: Discovering Residual Decompositions for MXFP4 Post-Training Quantization

arXiv:2609.34680v1 Announce Type: new Abstract: Four-bit post-training quantization can reduce the memory demands of large language models, but preserving accuracy under strict MXFP4 W4A4 requires coo

applicationsarxiv-cs-lg

Quasi Linear Kernel Attention with Infinite Capacity

arXiv:2609.35349v1 Announce Type: new Abstract: The evaluation cost of transformers with softmax attention scales quadratically with sequence length. Kernel attention addresses this by replacing softm

QuPID: Quantum Parameter-Efficient Input-Dependent Retrieval Adaptation for Medical RAG

arXiv:2609.33351v1 Announce Type: cross Abstract: Fidelity-based quantum retrieval ranks candidates by the fidelity between query and archive states. Applying a shared input-independent unitary after

Rate-Adaptive One-Step Diffusion Compression for AIGC Images

arXiv:2609.31795v1 Announce Type: new Abstract: We describe our entry to the LoViF 2026 AIGC Image Compression Challenge, a benchmark for ultra-low-bitrate coding of AI-generated images under a strict

ReAL: Accelerating Flow Matching through Segment Advancement with Shared Lookahead

arXiv:2609.33202v1 Announce Type: new Abstract: Flow-matching models generate high-quality images and videos, but repeated neural network evaluations make sampling expensive. Skipping evaluations redu

local-aiarxiv-cs-cv

REALM: A Coarse-to-Fine Generative Framework for Embodied Reactive Listening

arXiv:2609.33095v1 Announce Type: new Abstract: Generating responsive listener facial motion is an important task for embodied conversational AI. Two modeling challenges are central: accounting for th

local-aiarxiv-cs-ro

Applications

Recent Advances in Medical Imaging Segmentation: A Survey

arXiv:2505.09274v2 Announce Type: replace Abstract: Medical imaging is a cornerstone of modern healthcare, driving advancements in diagnosis, treatment planning, and patient care. Among its various ta

applicationsarxiv-cs-cv

Re:Cognize -- Open-Set Comic Character Re-Identification

arXiv:2609.34032v1 Announce Type: new Abstract: A manga reader meets a character on one page and knows them on sight a hundred pages later, without ever being handed a cast list. Re-identifying comic

Agents

Recursive Harness Distillation across Agents for Robot Manipulation

arXiv:2609.33378v1 Announce Type: cross Abstract: A central goal in robotics is to enable manipulation across changing tasks and environments. Vision-language-action (VLA) models provide broad manipul

agentsarxiv-cs-cv

ReGDiff: Guided Diffusion in Regulated Latent Space for Exploring Metamaterial Voxel Geometry

arXiv:2609.34231v1 Announce Type: new Abstract: Metamaterials are artificially engineered structures whose mechanical and physical behaviors are strongly shaped by geometry rather than composition. Vo

Region-Local Copula Evidence Fusion for Heterogeneous Remote Sensing Change Detection

arXiv:2609.32716v1 Announce Type: new Abstract: Superpixel copula models provide stable regional evidence for heterogeneous remote sensing change detection, but a single label per region limits locali

Reliable Replay through Spatial Coherence in Online Continual Learning

arXiv:2609.33725v1 Announce Type: cross Abstract: Continually adapting models to new tasks requires retaining earlier knowledge under limited memory and computation. Experience replay addresses this c

Residual Transferability in Neural Image Watermarking

arXiv:2609.32241v1 Announce Type: cross Abstract: Neural image watermarks can be forged by extracting watermark-bearing residuals from released images and transferring them to unrelated content. While

Applications

Rethinking Causal Action Tokenization with Conditional Annealing in Flow Matching

arXiv:2609.35469v1 Announce Type: cross Abstract: Autoregressive Vision-Language-Action (VLA) models offer a scalable path to robot learning, yet existing action tokenizers treat tokenization as a com

applicationsarxiv-cs-lg

Retracing Hodgkin and Huxley: State Recovery Does Not Certify Mechanism

arXiv:2609.34566v1 Announce Type: new Abstract: Predicting observed dynamics does not establish recovery of the underlying physical mechanism. Can machine learning retrace the hidden-state reasoning b

Revisiting Inexact Fixed-Point Iterations for Min-Max Problems: Stochasticity and Structured Nonconvexity

arXiv:2402.05071v3 Announce Type: replace-cross Abstract: We focus on constrained, L-smooth, potentially stochastic and nonconvex-nonconcave min-max problems either satisfying rho-cohypomonotonicity o

Revisiting Risky Tackle Detection with Vision Transformers

arXiv:2609.35562v1 Announce Type: new Abstract: This paper is a Track 2 reproducibility companion to an ICPR 2026 study on risky tackle detection in American football prac- tice videos. The original w

Reward-Aligned Reweighting for On-Policy Distillation

arXiv:2609.35517v1 Announce Type: new Abstract: On-policy distillation (OPD) trains a student language model with dense feedback from a stronger teacher on student-generated trajectories. Yet standard

Riemannian Difference-of-Convex Optimization for K-Means Clustering

arXiv:2609.34310v1 Announce Type: new Abstract: K-means is a widely adopted clustering approach in signal processing and machine learning. In this paper, we study K-means clustering through a cardinal

RLE-Bench: A Qualifying Exam for Coding Agents as Robot Learning Engineers

model-releasesarxiv-cs-ro

arXiv:2609.34210v1 Announce Type: new Abstract: Coding agents are beginning to move beyond purely digital tasks to tackle physical-world challenges, particularly in robotics. Existing robotics benchma

Robot-GST: geometry-aware spatial-temporal robot policy representation and evaluation

arXiv:2609.33872v1 Announce Type: cross Abstract: Robotic manipulation policies are advancing rapidly with increasing reliance on vision-language models for end-to-end decision making. However, reliab

Robust Bayesian Optimization with Q-Exponential Surrogates

arXiv:2609.32775v1 Announce Type: new Abstract: Bayesian optimization (BO) is a widely used framework for optimizing expensive black-box objectives, but standard BO methods often use Gaussian process

RoPE is Dead, Long Live RoPE: Towards Scalable Data-aware Positional Encodings

arXiv:2609.34556v1 Announce Type: cross Abstract: Transformers process tokens without any inherent notion of order, making positional encoding a fundamental requirement rather than an architectural re

Rotated Manifold Optimization for Low-Rank Adaptation

arXiv:2609.34264v1 Announce Type: new Abstract: We propose a novel optimizer for low-rank adaptation (LoRA) that explicitly incorporates the gauge symmetry of low-rank factorization. Our optimizer ext

RubiCap: Rubric-Guided Reinforcement Learning for Dense Image Captioning

arXiv:2603.09160v2 Announce Type: replace Abstract: Dense image captioning is critical for vision-language pretraining and for text-to-image generation, but scaling expert-quality annotations is prohi

safetyarxiv-cs-cv

Safety-Constrained Cascade Inference for Robust Malaria Cell Classification Under Field Corruptions

arXiv:2609.33005v1 Announce Type: new Abstract: Automated malaria diagnosis from thin blood-smear microscopy could meaningfully reduce the burden on under-resourced laboratories, but a model that maxi

safetyarxiv-cs-cv

SceneScaffold: Active Scene-State Construction for Unified 3D Scene Understanding

arXiv:2609.33518v1 Announce Type: new Abstract: Recent 3D large multimodal models (3D-LMMs) rely on a visual bottleneck to compress complex 3D scene evidence into a limited number of visual tokens com

SCORENF: Score-based Normalizing Flows for Sampling Unnormalized distributions

arXiv:2510.21330v2 Announce Type: replace Abstract: Unnormalized probability distributions are central to modeling complex physical systems across various scientific domains. Traditional sampling meth

Selective Fine-Tuning for Targeted and Robust Concept Unlearning

arXiv:2602.07919v2 Announce Type: replace-cross Abstract: Text guided diffusion models are used by millions of users, but can be easily exploited to produce harmful content. Concept unlearning methods

Shaping Persistent Representations from Independent Interactions

arXiv:2609.34604v1 Announce Type: new Abstract: World models learn environment dynamics from interaction experience. These dynamics depend on the current state and actions, as well as on properties th

Short-Length Code Designs for Integrated Sensing and Communications: A Deep Learning Approach

arXiv:2609.33605v1 Announce Type: new Abstract: Integrated sensing and communication (ISAC) enables joint communication and sensing using a shared waveform, but its signal design is challenging due to

Hardware

Single-Layer MeMo as a Randomized Hamming-Kernel Classifier

arXiv:2609.34562v1 Announce Type: new Abstract: MeMo (Zanzotto et al., 2025) is a recent language-model architecture that stores associations between token contexts and next tokens in a correlation ma

hardwarearxiv-cs-lg

SkillPE: Creativity-Oriented Cinematic Skill Evolution for Text-to-Video Prompt Engineering

arXiv:2609.34335v1 Announce Type: new Abstract: Achieving high-quality, cinematic results in text-to-video generation remains challenging for non-experts, whose prompts often lack professional narrati

Sol-H3: Recursive Self-Improvement for MiniMax-H3 Inference Acceleration on Sol-Engine across Cloud and Edge

arXiv:2609.35110v1 Announce Type: cross Abstract: Video diffusion models are rapidly scaling and exhibiting enhanced generation capabilities. Among these recent advancements, MiniMax-H3 stands out as

local-aiarxiv-cs-cv

SPACE: Sparse Predictive Attractor via Counterfactual Eviction for Streaming Video Memory

arXiv:2609.32592v1 Announce Type: new Abstract: Fixed-capacity streaming video memory requires repeated eviction decisions whose effects accumulate over time. Yet existing policies are evaluated prima

Sparse, self-organizing ensembles of local kernels detect rare statistical anomalies

arXiv:2511.03095v2 Announce Type: replace Abstract: Modern artificial intelligence has revolutionized how we extract representations from scientific data, yet the statistical properties of these repre

SpatialSpeak: QA-Native Reconstruction with Local and Global Context for Spatial Chain-of-Thought Reasoning

arXiv:2609.33616v1 Announce Type: new Abstract: Vision-language models (VLMs) can benefit from geometric priors for multi-view spatial reasoning, yet answer-only training does not directly supervise t

local-aiarxiv-cs-cv

Tutorials

SphMind: Towards Robust, Training-Free VLM-based Spatial Reasoning with a 360 Camera

arXiv:2609.33462v1 Announce Type: new Abstract: Omnidirectional or 360 cameras provide embodied AI agents with a holistic, wide field-of-view (FoV) view of their surroundings, motivating the use of Mu

tutorialsarxiv-cs-cv