Search: “tutorials”

FlowLM: Few-Step Language Modeling via Diffusion-to-Flow Adaptation

arXiv:2605.20199v1 Announce Type: new Abstract: We present FlowLM, a flow matching language model transformed from pre-trained diffusion language models via efficient fine-tuning. By re-aligning the c

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Head-Aware Key-Value Compression for Efficient Autoregressive Image Generation

DGX agent

arXiv:2605.20600v1 Announce Type: new Abstract: Autoregressive (AR) visual generation has achieved remarkable performance but suffers from high memory usage and low throughput, as it requires caching

tutorialsarxiv-cs-cv

21 May 2026

HyDAR-Pano3D: A Hybrid Disentangled Anatomical Recovery Framework for Panoramic-to-3D Reconstruction

arXiv:2605.20827v1 Announce Type: new Abstract: Panoramic radiograph (PR) is fundamentally used in routine dental care, but it inherently provides only a two-dimensional (2D) projection of complex thr

Introspective X Training: Feedback Conditioning Improves Scaling Across all LLM Training Stages

arXiv:2605.20285v1 Announce Type: new Abstract: We tackle the question of how to scale more efficiently across the many, ever-growing stages of current LLM training pipelines. Our guiding intuition st

iTryOn: Mastering Interactive Video Virtual Try-On with Spatial-Semantic Guidance

arXiv:2605.21431v1 Announce Type: new Abstract: Video Virtual Try-On (VVT) aims to seamlessly replace a garment on a person in a video with a new one. While existing methods have made significant stri

Jointly Learning Predicates and Actions Enables Zero-Shot Skill Composition

arXiv:2605.20648v1 Announce Type: new Abstract: Learning from Demonstration (LfD) enables robots to learn complex behaviors from expert examples, yet existing approaches often fail to generalize to ne

tutorialsarxiv-cs-ro

Latent Process Generator Matching

arXiv:2605.20547v1 Announce Type: new Abstract: Many recent flow-matching and diffusion-style generative models rely on auxiliary stochastic dynamics during training: a richer process is simulated to

Learning to Defer in Non-Stationary Time Series via Switching State-Space Models

arXiv:2601.22538v2 Announce Type: replace Abstract: Learning-to-defer (L2D) routes each decision to a system's own predictor or to an external expert. Streaming time-series settings break the offline-

Let EEG Models Learn EEG

arXiv:2605.21280v1 Announce Type: new Abstract: High-fidelity EEG generation is critical for alleviating data scarcity and addressing privacy constraints in large-scale neural modeling. Despite recent

LT2: Linear-Time Looped Transformers

arXiv:2605.20670v1 Announce Type: new Abstract: Looped Transformers (LT) have emerged as a powerful architecture by iterating their layers multiple times before decoding the final token. However, pair

Memorisation, convergence and generalisation in generative models

arXiv:2605.21402v1 Announce Type: cross Abstract: Generative neural networks learn how to produce highly realistic images from a large, but finite number of examples - or do they simply memorise their

On the Regularity and Generalization of One-Step Wasserstein-guided Generative Models for PDE-Induced Measures

arXiv:2605.21388v1 Announce Type: new Abstract: Despite the remarkable empirical success of generative models, the available theory on their statistical accuracy in scientific computing remains largel

PACD-Net: Pseudo-Augmented Contrastive Distillation for Glycemic Control Estimation from SMBG

arXiv:2605.20751v1 Announce Type: new Abstract: Effective diabetes management requires continuous monitoring of glycemic levels. Clinically, glycemic control is assessed using metrics such as Time in

Pseudo-Siamese Network for Planning in Target-Oriented Proactive Dialogues

arXiv:2605.20195v1 Announce Type: new Abstract: A target-oriented proactive dialogue system is designed to steer conversations toward predefined targets while actively providing suggestions. The core

Puzzled By ChatGPT? No more! A Jigsaw Puzzle to Promote AI Literacy and Awareness

arXiv:2605.20404v1 Announce Type: new Abstract: The rapid adoption of Generative AI, including LLM-based chatbots like ChatGPT, has highlighted the need for accessible ways to support public understan

Q-Net: Queue Length Estimation via Kalman-based Neural Networks

arXiv:2509.24725v3 Announce Type: replace Abstract: Estimating queue lengths at signalized intersections is a long-standing challenge in traffic management. Partial observability of vehicle flows comp

Reducing Object Hallucination in LVLMs via Emphasizing Image-negative Tokens

arXiv:2605.21300v1 Announce Type: new Abstract: Object hallucination is a significant challenge that hinders the application of large vision-language models (LVLMs) in practice. We hypothesize that on

Task-Routed Mixture-of-Experts with Cognitive Appraisal for Implicit Sentiment Analysis

arXiv:2605.20916v1 Announce Type: new Abstract: Implicit sentiment analysis is challenging because sentiment toward an aspect is often inferred from events rather than expressed through explicit opini

Towards Understanding Self-Pretraining for Sequence Classification

arXiv:2605.21070v1 Announce Type: new Abstract: Amos et al. (2024) showed that the accuracy of Transformer models in sequence classification can be significantly improved by first pretraining with a m

Verification of Unknown Dynamical Systems via Autoencoder Latent Space

arXiv:2512.13593v4 Announce Type: replace Abstract: Formal verification provides a powerful framework for proving that dynamical systems satisfy their specifications. However, these techniques face sc

WiXus: A Wheeled-Legged Robot with Wire-Driven Environmental Utilizing to Integrate Mobility and Manipulation

arXiv:2605.20932v1 Announce Type: new Abstract: Wheeled-legged robots, which have wheels at their feet and achieve high mobility by coordinating wheel drive and leg drive, have been developed. These r

tutorialsarxiv-cs-ro

A Multi-Dimensional Clustering Approach for Identifying Inborn Errors of Immunity

arXiv:2605.18880v1 Announce Type: cross Abstract: Rare diseases such as inborn errors of immunity (IEI) require early diagnosis to prevent end organ damage and improve quality of life. Hurdles in acce

Activation Functions, Statistics and Learning of Higher-Order Interactions in Restricted Boltzmann Machines

arXiv:2605.19178v1 Announce Type: cross Abstract: The great success of neural networks in recognizing hidden patterns and correlations in complex data lies in the way they take advantage of the large

Bayesian Symbolic Regression for Missing Physics

arXiv:2603.14918v2 Announce Type: replace-cross Abstract: Model-based approaches for (bio)process systems often suffer from incomplete knowledge of the underlying physical, chemical, or biological law

BCI-sift: An automated feature selection toolbox for Brain Computer Interface applications

arXiv:2605.19646v1 Announce Type: cross Abstract: Advancements in clinical Brain-Computer Interfaces (BCIs) depend on precise and reliable signal interpretation. However, the high-dimensional and nois

Beyond Rational Illusion: Behaviorally Realistic Strategic Classification

arXiv:2605.19674v1 Announce Type: new Abstract: Strategic classification(SC) studies the interaction between decision models and agents who strategically manipulate their features for favorable outcom

CANINE: Coaching Visually Impaired Users for Interactive Navigation with a Robot Guide Dog

arXiv:2605.19501v1 Announce Type: cross Abstract: Robot guide dogs offer navigation assistance that greatly expands the independent mobility of the visually impaired, but their effective use requires

Character-Centered Dialogue Generation from Scene-Level Prompts

arXiv:2505.16819v4 Announce Type: replace Abstract: Recent advances in scene-based video generation enable coherent visual narratives from structured prompts, yet a key aspect of storytelling -- chara

Critique-Guided Distillation for Robust Reasoning via Refinement

arXiv:2505.11628v4 Announce Type: replace Abstract: Supervised fine-tuning with expert demonstrations often produces models that imitate outputs without internalizing the reasoning processes needed fo

Data-centric Design of Learning-based Surgical Gaze Perception Models in Multi-Task Simulation

arXiv:2602.09259v2 Announce Type: replace Abstract: In robot-assisted minimally invasive surgery (RMIS), reduced haptic feedback and depth cues increase reliance on expert visual perception, motivatin

tutorialsarxiv-cs-ro

Decoding Rewards in Competitive Games: Inverse Game Theory with Entropy Regularization

arXiv:2601.12707v2 Announce Type: replace Abstract: Estimating the unknown reward functions driving agents' behaviors is of central interest in inverse reinforcement learning and game theory. To tackl

Diagnosing Multi-step Reasoning Failures in Black-box LLMs via Stepwise Confidence Attribution

arXiv:2605.19228v1 Announce Type: cross Abstract: Large Language Models have achieved strong performance on reasoning tasks with objective answers by generating step-by-step solutions, but diagnosing

Diffusion and Flow-based Copulas: Forgetting and Remembering Dependencies

arXiv:2509.19707v2 Announce Type: replace-cross Abstract: Copulas are a fundamental tool for modelling multivariate dependencies in data, forming the method of choice in diverse fields and application

Diffusion Graph Posterior Sampling for Nonlinear Inverse Problems with Application to Electrical Impedance Tomography

arXiv:2605.19621v1 Announce Type: cross Abstract: Deep generative models have emerged as state-of-the-art for solving inverse problems, but applying them to inverse problems for PDEs, like electrical

DOTRAG: Retrieval-Time Reasoning Along Paths

arXiv:2605.18760v1 Announce Type: cross Abstract: Graph Retrieval-Augmented Generation (GraphRAG) is dominated by a retrieve-then-reason paradigm, where context is retrieved using heuristics and then

Drifting Objectives for Refining Discrete Diffusion Language Models

arXiv:2605.19470v1 Announce Type: new Abstract: Discrete diffusion language models (DDLMs) generate text by iteratively denoising categorical token sequences, while recent drifting methods for continu

Evaluating Memory Condensation Strategies for Coding Agents in Data-Driven Scientific Discovery

arXiv:2605.18854v1 Announce Type: new Abstract: Coding agents accumulate extensive context during long-running tasks, yet fixed context windows force practitioners to choose between truncation and tas

FAWN: A MultiEncoder Fusion-Attention Wave Network for Integrated Sensing and Communication Indoor Scene Inference

arXiv:2509.14968v3 Announce Type: replace Abstract: The upcoming generations of wireless technologies promise an era where everything is interconnected and intelligent. As the need for intelligence gr

FreeOrbit4D: Training-Free Arbitrary Camera Redirection for Monocular Videos via Foreground-Complete 4D Reconstruction

arXiv:2601.18993v2 Announce Type: replace-cross Abstract: Camera redirection aims to replay a dynamic scene from a single monocular video under a user-specified camera trajectory. However, large-angle

Generative Pseudo-Force Fields for Molecular Generation

arXiv:2605.19050v1 Announce Type: new Abstract: Generating stable molecular conformations typically forces a tradeoff between the physical realism of energy-based relaxation and the sampling efficienc

Heterogeneity-Aware Dataset Scheduling for Efficient Audio Large Language Model Training

arXiv:2605.19101v1 Announce Type: cross Abstract: Training general-purpose Audio Large Language Models (ALLMs) across diverse datasets is essential for holistic audio understanding, yet it faces signi

Hierarchical Contrastive Learning for Multi-Domain Protein-Ligand Binding

arXiv:2605.19902v1 Announce Type: new Abstract: Predicting protein-ligand binding affinity remains intractable for multi-domain proteins, where inter-domain dynamics govern molecular recognition. Exis

IMPACT: Influence Modeling for Open-Set Time Series Anomaly Detection

arXiv:2603.29183v2 Announce Type: replace-cross Abstract: Open-set anomaly detection (OSAD) is an emerging paradigm designed to utilize limited labeled data from anomaly classes seen in training to id

INAR-VL: Input-Aware Routing for Edge-Cloud Vision-Language Inference

arXiv:2605.18853v1 Announce Type: cross Abstract: Edge deployment of Vision-Language Models (VLMs) faces a tradeoff between latency and accuracy: cloud execution provides high-quality predictions but

KAN-MLP-Mixer: A comprehensive investigation of the usage of Kolmogorov-Arnold Networks (KANs) for improving IMU-based Human Activity Recognition

arXiv:2605.19031v1 Announce Type: new Abstract: Kolmogorov-Arnold Networks (KANs) have demonstrated an exceptional ability to learn complex functions on clean, low-dimensional data but struggle to mai

Language Model Memory and Memory Models for Language

arXiv:2602.13466v2 Announce Type: replace-cross Abstract: The ability of machine learning models to store input information in hidden layer vector embeddings, analogous to the concept of `memory', is

Language models struggle with compartmentalization

arXiv:2605.19284v1 Announce Type: new Abstract: In the training data used by large language models (LLMs), the same latent concept is often presented in multiple distinct ways: the same facts appear i

Latent Laplace Diffusion for Irregular Multivariate Time Series

arXiv:2605.19805v1 Announce Type: cross Abstract: Irregular multivariate time series impose a trade-off for long-horizon forecasting: discrete methods can distort temporal structure via re-gridding, w