Search: “research”

Beyond the Mean: Modelling Annotation Distributions in Continuous Affect Prediction

arXiv:2604.07198v1 Announce Type: new Abstract: Emotion annotation is inherently subjective and cognitively demanding, producing signals that reflect diverse perceptions across annotators rather than

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Bi-level Heterogeneous Learning for Time Series Foundation Models: A Federated Learning Approach

DGX agent

arXiv:2604.06727v1 Announce Type: new Abstract: Heterogeneity in time series data is more pronounced than in vision or language, as temporal dynamics vary substantially across domains and tasks. Exist

researcharxiv-cs-lg

10 Apr 2026

Bi-Level Optimization for Single Domain Generalization

arXiv:2604.06349v1 Announce Type: cross Abstract: Generalizing from a single labeled source domain to unseen target domains, without access to any target data during training, remains a fundamental ch

Bi-Lipschitz Autoencoder With Injectivity Guarantee

arXiv:2604.06701v1 Announce Type: new Abstract: Autoencoders are widely used for dimensionality reduction, based on the assumption that high-dimensional data lies on low-dimensional manifolds. Regular

Bird-Inspired Spatial Flapping Wing Mechanism via Coupled Linkages with Single Actuator

arXiv:2604.07677v1 Announce Type: new Abstract: Spatial single-loop mechanisms such as Bennett linkages offer a unique combination of one-degree-of-freedom actuation and nontrivial spatial trajectorie

BLaDA: Bridging Language to Functional Dexterous Actions within 3DGS Fields

arXiv:2604.08410v1 Announce Type: new Abstract: In unstructured environments, functional dexterous grasping calls for the tight integration of semantic understanding, precise 3D functional localizatio

Bridging MRI and PET physiology: Untangling complementarity through orthogonal representations

arXiv:2604.07154v1 Announce Type: cross Abstract: Multimodal imaging analysis often relies on joint latent representations, yet these approaches rarely define what information is shared versus modalit

Busemann energy-based attention for emotion analysis in Poincare discs

arXiv:2604.06752v1 Announce Type: new Abstract: We present EmBolic - a novel fully hyperbolic deep learning architecture for fine-grained emotion analysis from textual messages. The underlying idea is

CAAP: Capture-Aware Adversarial Patch Attacks on Palmprint Recognition Models

arXiv:2604.06987v1 Announce Type: cross Abstract: Palmprint recognition is deployed in security-critical applications, including access control and palm-based payment, due to its contactless acquisiti

ChangeBridge: Spatiotemporal Image Generation with Multimodal Controls for Remote Sensing

arXiv:2507.04678v3 Announce Type: replace Abstract: Spatiotemporal image generation is a highly meaningful task, which can generate future scenes conditioned on given observations. However, existing c

ChopGrad: Pixel-Wise Losses for Latent Video Diffusion via Truncated Backpropagation

arXiv:2603.17812v2 Announce Type: replace-cross Abstract: Recent video diffusion models achieve high-quality generation through recurrent frame processing where each frame generation depends on previo

Clickbait detection: quick inference with maximum impact

arXiv:2604.08148v1 Announce Type: new Abstract: We propose a lightweight hybrid approach to clickbait detection that combines OpenAI semantic embeddings with six compact heuristic features capturing s

Compact Example-Based Explanations for Language Models

arXiv:2601.03786v2 Announce Type: replace Abstract: Training data influence estimation methods quantify the contribution of training documents to a model's output, making them a promising source of in

Complementary Filtering on SO(3) for Attitude Estimation with Scalar Measurements

arXiv:2604.08099v1 Announce Type: cross Abstract: Attitude estimation using scalar measurements, corresponding to partial vectorial observations, arises naturally when inertial vectors are not fully o

Component-Adaptive and Lesion-Level Supervision for Improved Small Structure Segmentation in Brain MRI

arXiv:2604.08015v1 Announce Type: new Abstract: We propose a unified objective function, termed CATMIL, that augments the base segmentation loss with two auxiliary supervision terms operating at diffe

Compressible Softmax-Attended Language under Incompressible Attention

arXiv:2604.04384v2 Announce Type: replace-cross Abstract: Softmax attention defines an interaction through d_h head dimensions, but not all dimensions carry equal weight once real text passes throug

Computational bottlenecks for denoising diffusions

arXiv:2503.08028v3 Announce Type: replace-cross Abstract: Denoising diffusions sample from a probability distribution mu in R^d by constructing a stochastic process $({hat{oldsymbol x

Contraction-Aligned Analysis of Soft Bellman Residual Minimization with Weighted Lp-Norm for Markov Decision Problem

arXiv:2604.06837v1 Announce Type: new Abstract: The problem of solving Markov decision processes under function approximation remains a fundamental challenge, even under linear function approximation

Controller Design for Structured State-space Models via Contraction Theory

arXiv:2604.07069v1 Announce Type: cross Abstract: This paper presents an indirect data-driven output feedback controller synthesis for nonlinear systems, leveraging Structured State-space Models (SSMs

Tutorials

Coordinate-Based Dual-Constrained Autoregressive Motion Generation

arXiv:2604.08088v1 Announce Type: new Abstract: Text-to-motion generation has attracted increasing attention in the research community recently, with potential applications in animation, virtual reali

tutorialsarxiv-cs-cv

Cost-Efficient Multi-Scale Fovea for Semantic-Based Visual Search Attention

arXiv:2604.03836v2 Announce Type: replace-cross Abstract: Semantics are one of the primary sources of top-down preattentive information. Modern deep object detectors excel at extracting such valuable

Countering the Over-Reliance Trap: Mitigating Object Hallucination for LVLMs via a Self-Validation Framework

arXiv:2601.22451v2 Announce Type: replace-cross Abstract: Despite progress in Large Vision Language Models (LVLMs), object hallucination remains a critical issue in image captioning task, where models

Cram Less to Fit More: Training Data Pruning Improves Memorization of Facts

arXiv:2604.08519v1 Announce Type: new Abstract: Large language models (LLMs) can struggle to memorize factual knowledge in their parameters, often leading to hallucinations and poor performance on kno

Cross-Tokenizer LLM Distillation through a Byte-Level Interface

arXiv:2604.07466v1 Announce Type: new Abstract: Cross-tokenizer distillation (CTD), the transfer of knowledge from a teacher to a student language model when the two use different tokenizers, remains

CRPS-Optimal Binning for Univariate Conformal Regression

arXiv:2603.22000v2 Announce Type: replace Abstract: We propose a method for non-parametric conditional distribution estimation based on partitioning covariate-sorted observations into contiguous bins

Current LLMs still cannot 'talk much' about grammar modules: Evidence from syntax

arXiv:2603.20114v4 Announce Type: replace Abstract: We aim to examine the extent to which Large Language Models (LLMs) can 'talk much' about grammar modules, providing evidence from syntax core proper

DailyArt: Discovering Articulation from Single Static Images via Latent Dynamics

arXiv:2604.07758v1 Announce Type: new Abstract: Articulated objects are essential for embodied AI and world models, yet inferring their kinematics from a single closed-state image remains challenging

Database Querying under Missing Values Governed by Missingness Mechanisms

arXiv:2604.06520v1 Announce Type: cross Abstract: We address the problems of giving a semantics to- and doing query answering (QA) on a relational database (RDB) that has missing values (MVs). The cau

DeCo: Frequency-Decoupled Pixel Diffusion for End-to-End Image Generation

arXiv:2511.19365v2 Announce Type: replace-cross Abstract: Pixel diffusion aims to generate images directly in pixel space in an end-to-end fashion. This approach avoids the limitations of VAE in the t

Depression Detection at the Point of Care: Automated Analysis of Linguistic Signals from Routine Primary Care Encounters

arXiv:2604.06193v1 Announce Type: cross Abstract: Depression is underdiagnosed in primary care, yet timely identification remains critical. Recorded clinical encounters, increasingly common with digit

Development of ML model for triboelectric nanogenerator based sign language detection system

arXiv:2604.06220v1 Announce Type: cross Abstract: Sign language recognition (SLR) is vital for bridging communication gaps between deaf and hearing communities. Vision-based approaches suffer from occ

DHFP-PE: Dual-Precision Hybrid Floating Point Processing Element for AI Acceleration

arXiv:2604.04507v2 Announce Type: replace-cross Abstract: The rapid adoption of low-precision arithmetic in artificial intelligence and edge computing has created a strong demand for energy-efficient

DietDelta: A Vision-Language Approach for Dietary Assessment via Before-and-After Images

arXiv:2604.06352v1 Announce Type: cross Abstract: Accurate dietary assessment is critical for precision nutrition, yet most image-based methods rely on a single pre-consumption image and provide only

Differentially Private Language Generation and Identification in the Limit

arXiv:2604.08504v1 Announce Type: cross Abstract: We initiate the study of language generation in the limit, a model recently introduced by Kleinberg and Mullainathan [KM24], under the constraint of d

Diffusion Language Models Know the Answer Before Decoding

arXiv:2508.19982v5 Announce Type: replace Abstract: Diffusion language models (DLMs) have recently emerged as an alternative to autoregressive approaches, offering parallel sequence generation and fle

DiffVC: A Non-autoregressive Framework Based on Diffusion Model for Video Captioning

arXiv:2604.08084v1 Announce Type: new Abstract: Current video captioning methods usually use an encoder-decoder structure to generate text autoregressively. However, autoregressive methods have inhere

DINO-QPM: Adapting Visual Foundation Models for Globally Interpretable Image Classification

arXiv:2604.07166v1 Announce Type: cross Abstract: Although visual foundation models like DINOv2 provide state-of-the-art performance as feature extractors, their complex, high-dimensional representati

DisCEdge: Distributed Context Management for Large Language Models at the Edge

arXiv:2511.22599v2 Announce Type: replace-cross Abstract: Deploying Large Language Model (LLM) services at the edge benefits latency-sensitive and privacy-aware applications. However, the stateless na

Distilling Specialized Orders for Visual Generation

arXiv:2504.17069v2 Announce Type: replace Abstract: Autoregressive (AR) image generators are becoming increasingly popular due to their ability to produce high-quality images and their scalability. Ty

DIVERSED: Relaxed Speculative Decoding via Dynamic Ensemble Verification

arXiv:2604.07622v1 Announce Type: new Abstract: Speculative decoding is an effective technique for accelerating large language model inference by drafting multiple tokens in parallel. In practice, its

DMin: Scalable Training Data Influence Estimation for Diffusion Models

arXiv:2412.08637v4 Announce Type: replace Abstract: Identifying the training data samples that most influence a generated image is a critical task in understanding diffusion models (DMs), yet existing

Do We Need Distinct Representations for Every Speech Token? Unveiling and Exploiting Redundancy in Large Speech Language Models

arXiv:2604.06871v1 Announce Type: cross Abstract: Large Speech Language Models (LSLMs) typically operate at high token rates (tokens/s) to ensure acoustic fidelity, yet this results in sequence length

'Don't Do That!': Guiding Embodied Systems through Large Language Model-based Constraint Generation

arXiv:2506.04500v3 Announce Type: replace-cross Abstract: Recent advancements in large language models (LLMs) have spurred interest in robotic navigation that incorporates complex spatial, mathematica

Double: Breaking the Acceleration Limit via Double Retrieval Speculative Parallelism

arXiv:2601.05524v2 Announce Type: replace Abstract: Parallel Speculative Decoding (PSD) accelerates traditional Speculative Decoding (SD) by overlapping draft generation with verification. However, it

DP-DeGauss: Dynamic Probabilistic Gaussian Decomposition for Egocentric 4D Scene Reconstruction

arXiv:2604.07986v1 Announce Type: new Abstract: Egocentric video is crucial for next-generation 4D scene reconstruction, with applications in AR/VR and embodied AI. However, reconstructing dynamic fir

Drifting Fields are not Conservative

arXiv:2604.06333v1 Announce Type: new Abstract: Drifting models generate high-quality samples in a single forward pass by transporting generated samples toward the data distribution using a vector val

DYCP: Dynamic Context Pruning for Long-Form Dialogue with LLMs

arXiv:2601.07994v4 Announce Type: replace Abstract: Large Language Models (LLMs) increasingly operate over long-form dialogues with frequent topic shifts. While recent LLMs support extended context wi

E-3DPSM: A State Machine for Event-Based Egocentric 3D Human Pose Estimation

arXiv:2604.08543v1 Announce Type: new Abstract: Event cameras offer multiple advantages in monocular egocentric 3D human pose estimation from head-mounted devices, such as millisecond temporal resolut