Search: “research”

Eluder dimension: localise it!

arXiv:2601.09825v2 Announce Type: replace Abstract: We establish a lower bound on the eluder dimension of generalised linear model classes, showing that standard eluder dimension-based analysis cannot

EmbodiedHead: Real-Time Listening and Speaking Avatar for Conversational Agents

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arXiv:2604.17211v1 Announce Type: new Abstract: We present EmbodiedHead, a speech-driven talking-head framework that equips LLMs with real-time visual avatars for conversation. A practical embodied av

researcharxiv-cs-cv

21 Apr 2026

Emergent Structured Representations Support Flexible In-Context Inference in Large Language Models

arXiv:2602.07794v3 Announce Type: replace Abstract: Large language models (LLMs) exhibit emergent behaviors suggestive of human-like reasoning. While recent work has identified structured conceptual r

emg2speech: Synthesizing speech from electromyography using self-supervised speech models

arXiv:2510.23969v2 Announce Type: replace-cross Abstract: We present a neuromuscular speech interface that translates electromyographic (EMG) signals recorded from orofacial muscles during speech arti

Emotion Collider: Dual Hyperbolic Mirror Manifolds for Sentiment Recovery via Anti Emotion Reflection

arXiv:2602.16161v3 Announce Type: replace-cross Abstract: Emotional expression underpins natural communication and effective human-computer interaction. We present Emotion Collider (EC-Net), a hyperbo

EmoVerse: A MLLMs-Driven Emotion Representation Dataset for Interpretable Visual Emotion Analysis

arXiv:2511.12554v2 Announce Type: replace Abstract: Visual Emotion Analysis (VEA) aims to bridge the affective gap between visual content and human emotional responses. Despite its promise, progress i

En 2021, les opposants à la vaccination craignaient 'une hécatombe' dans les années à venir. Nous sommes 5 ans plus tard et une immense étud…

En 2021, les opposants à la vaccination craignaient 'une hécatombe' dans les années à venir. Nous sommes 5 ans plus tard et une immense étude sur les données de 29 millions de Français (23 millions va

researchyann-lecun--x

Enabling Stroke-Level Structural Analysis of Hieroglyphic Scripts without Language-Specific Priors

arXiv:2601.05508v2 Announce Type: replace-cross Abstract: Hieroglyphs, as logographic writing systems, encode rich semantic and cultural information within their internal structural composition. Yet,

Enhancing Anomaly-Based Intrusion Detection Systems with Process Mining

arXiv:2604.18066v1 Announce Type: cross Abstract: Anomaly-based Intrusion Detection Systems (IDSs) ensure protection against malicious attacks on networked systems. While deep learning-based IDSs achi

Enhancing classification accuracy through chaos

arXiv:2603.15299v2 Announce Type: replace Abstract: We propose a novel approach which exploits chaos to enhance classification accuracy. Specifically, the available data that need to be classified are

Enhancing Trust in Large Language Models via Uncertainty-Calibrated Fine-Tuning

arXiv:2412.02904v2 Announce Type: replace Abstract: Large language models (LLMs) have revolutionized the field of natural language processing with their impressive reasoning and question-answering cap

Enhancing Zero-shot Personalized Image Aesthetics Assessment with Profile-aware Multimodal LLM

arXiv:2604.17233v1 Announce Type: new Abstract: Personalized image aesthetics assessment (PIAA) aims to predict an individual user's subjective rating of an image, which requires modeling user-specifi

Erase to Improve: Erasable Reinforcement Learning for Search-Augmented LLMs

arXiv:2510.00861v2 Announce Type: replace Abstract: While search-augmented large language models (LLMs) exhibit impressive capabilities, their reliability in complex multi-hop reasoning remains limite

Establishing a Scale for Kullback-Leibler Divergence in Language Models Across Various Settings

arXiv:2505.15353v3 Announce Type: replace Abstract: Log-likelihood vectors define a common space for comparing language models as probability distributions, enabling unified comparisons across heterog

Estimating Commonsense Plausibility through Semantic Shifts

arXiv:2502.13464v2 Announce Type: replace Abstract: Commonsense plausibility estimation is critical for evaluating language models (LMs), yet existing generative approaches--reliant on likelihoods or

Evalet: Evaluating Large Language Models through Functional Fragmentation

arXiv:2509.11206v4 Announce Type: replace-cross Abstract: Practitioners increasingly rely on Large Language Models (LLMs) to evaluate generative AI outputs through 'LLM-as-a-Judge' approaches. However

Evaluating Temporal and Structural Anomaly Detection Paradigms for DDoS Traffic

arXiv:2604.16575v1 Announce Type: new Abstract: Unsupervised anomaly detection is widely used to detect Distributed Denial-of-Service (DDoS) attacks in cloud-native 5G networks, yet most studies assum

Evaluating the Impact of Verbal Multiword Expressions on Machine Translation

arXiv:2508.17458v2 Announce Type: replace Abstract: Verbal multiword expressions (VMWEs) remain difficult for machine translation because their meanings are often not recoverable from their component

EvoComp: Learning Visual Token Compression for Multimodal Large Language Models via Semantic-Guided Evolutionary Labeling

arXiv:2604.17087v1 Announce Type: new Abstract: Recent Multimodal Large Language Models (MLLMs) have demonstrated strong performance on vision-language understanding tasks, yet their inference efficie

ExAI5G: A Logic-Based Explainable AI Framework for Intrusion Detection in 5G Networks

arXiv:2604.18052v1 Announce Type: cross Abstract: Intrusion detection systems (IDSs) for 5G networks must handle complex, high-volume traffic. Although opaque 'black-box' models can achieve high accur

Examining Fast Radiatively Driven Responses Using Machine-Learning Weather Emulators

arXiv:2602.16090v2 Announce Type: replace-cross Abstract: The response of the climate system to increased greenhouse gases and other radiative perturbations is governed by a combination of fast and sl

Exploring Concreteness Through a Figurative Lens

arXiv:2604.18296v1 Announce Type: new Abstract: Static concreteness ratings are widely used in NLP, yet a word's concreteness can shift with context, especially in figurative language such as metaphor

Exploring Mutual Cross-Modal Attention for Context-Aware Human Affordance Generation

arXiv:2502.13637v2 Announce Type: replace Abstract: Human affordance learning investigates contextually relevant novel pose prediction such that the estimated pose represents a valid human action with

Expressing Social Emotions: Misalignment Between LLMs and Human Cultural Emotion Norms

arXiv:2604.16757v1 Announce Type: new Abstract: The expression of emotions that serve social purposes, such as asserting independence or fostering interdependence, is central to human interactions and

Expressive yet Efficient Feature Expansion with Adaptive Cross-Hadamard Products

arXiv:2505.22226v2 Announce Type: replace Abstract: Recent theoretical advances reveal that the Hadamard product induces nonlinear representations and implicit high-dimensional mappings for the field

Extraction of informative statistical features in the problem of forecasting time series generated by It{o}-type processes

arXiv:2604.16865v1 Announce Type: cross Abstract: In this paper, we consider the problem of extraction of most informative features from time series that are regarded as observed values of stochastic

Fast Online 3D Multi-Camera Multi-Object Tracking and Pose Estimation

arXiv:2604.16522v1 Announce Type: new Abstract: This paper proposes a fast and online method for jointly performing 3D multi-object tracking and pose estimation using multiple monocular cameras. Our a

Faster by Design: Interactive Aerodynamics via Neural Surrogates Trained on Expert-Validated CFD

arXiv:2604.18491v1 Announce Type: new Abstract: Computational Fluid Dynamics (CFD) is central to race-car aerodynamic development, yet its cost -- tens of thousands of core-hours per high-fidelity eva

FlowRefiner: Flow Matching-Based Iterative Refinement for 3D Turbulent Flow Simulation

arXiv:2604.17149v1 Announce Type: cross Abstract: Accurate autoregressive prediction of 3D turbulent flows remains challenging for neural PDE solvers, as small errors in fine-scale structures can accu

FoleyDirector: Fine-Grained Temporal Steering for Video-to-Audio Generation via Structured Scripts

arXiv:2603.19857v2 Announce Type: replace-cross Abstract: Recent Video-to-Audio (V2A) methods have achieved remarkable progress, enabling the synthesis of realistic, high-quality audio. However, they

Follow the Path: Reasoning over Knowledge Graph Paths to Improve Large Language Model Factuality

arXiv:2505.11140v3 Announce Type: replace Abstract: We introduce fs1, a simple yet effective method that improves the factuality of reasoning traces by collecting them from large reasoning models and

Forget What Matters, Keep the Rest: Selective Unlearning of Informative Tokens

arXiv:2604.17785v1 Announce Type: new Abstract: Unlearning in large language models (LLMs) has emerged as a promising safeguard against adversarial behaviors. When the forgetting loss is applied unifo

Foundational Study on Authorship Attribution of Japanese Web Reviews for Actor Analysis

arXiv:2604.16376v1 Announce Type: new Abstract: This study investigates the applicability of authorship attribution based on stylistic features to support actor analysis in threat intelligence. As a f

FrameDiT: Diffusion Transformer with Matrix Attention for Efficient Video Generation

arXiv:2603.09721v2 Announce Type: replace Abstract: High-fidelity video generation remains challenging for diffusion models due to the difficulty of modeling complex spatio-temporal dynamics efficient

FrameVGGT: Geometry-Aligned Frame-Level Memory for Bounded Streaming VGGT

arXiv:2603.07690v2 Announce Type: replace Abstract: Streaming Visual Geometry Transformers such as StreamVGGT enable strong online 3D perception, but their KV-cache grows unbounded over long streams,

Frequency-guided Multi-level Reasoning for Scene Graph Generation in Video

arXiv:2604.17298v1 Announce Type: new Abstract: Video Scene Graph Generation aims to obtain structured semantic representations of objects and their relationships in videos for high-level understandin

From 2:4 to 8:16 sparsity patterns in LLMs for Outliers and Weights with Variance Correction

arXiv:2507.03052v2 Announce Type: replace Abstract: As large language models (LLMs) grow in size, efficient compression techniques like quantization and sparsification are critical. While quantization

From Attribution to Abstention: Training-Free Attention-Based Auditing for Clinical Summarization

arXiv:2601.16397v2 Announce Type: replace Abstract: Deploying multimodal large language models (MLLMs) for clinical summarization demands not only fluent generation but also transparency about where e

From Classical to Quantum: Extending Prometheus for Unsupervised Discovery of Phase Transitions in Three Dimensions and Quantum Systems

arXiv:2602.14928v4 Announce Type: replace-cross Abstract: We extend the Prometheus framework for unsupervised phase transition discovery from two-dimensional classical systems to three-dimensional cla

From Domains to Instances: Dual-Granularity Data Synthesis for LLM Unlearning

arXiv:2601.04278v2 Announce Type: replace Abstract: Although machine unlearning is essential for removing private, harmful, or copyrighted content from LLMs, current benchmarks often fail to faithfull

From Fallback to Frontline: When Can LLMs be Superior Annotators of Human Perspectives?

arXiv:2604.17968v1 Announce Type: cross Abstract: Although large language models (LLMs) are increasingly used as annotators at scale, they are typically treated as a pragmatic fallback rather than a f

From Implicit to Explicit: Token-Efficient Logical Supervision for Mathematical Reasoning in LLMs

arXiv:2601.03682v2 Announce Type: replace Abstract: Recent studies reveal that large language models (LLMs) exhibit limited logical reasoning abilities in mathematical problem-solving, instead often r

From User Recognition to Activity Counting: An Identity-Agnostic Approach to Multi-User WiFi Sensing

arXiv:2604.16572v1 Announce Type: new Abstract: Wi-Fi Channel State Information (CSI) enables device-free human activity recognition, but existing multi-user approaches assume a fixed set of known use

From Verbatim to Gist: Distilling Pyramidal Multimodal Memory via Semantic Information Bottleneck for Long-Horizon Video Agents

arXiv:2603.01455v2 Announce Type: replace-cross Abstract: While multimodal large language models have demonstrated impressive short-term reasoning, they struggle with long-horizon video understanding

G-PARC: Graph-Physics Aware Recurrent Convolutional Neural Networks for Spatiotemporal Dynamics on Unstructured Meshes

arXiv:2604.16533v1 Announce Type: new Abstract: Physics-aware recurrent convolutional networks (PARC) have demonstrated strong performance in predicting nonlinear spatiotemporal dynamics by embedding

GaLa: Hypergraph-Guided Visual Language Models for Procedural Planning

arXiv:2604.17241v1 Announce Type: new Abstract: Implicit spatial relations and deep semantic structures encoded in object attributes are crucial for procedural planning in embodied AI systems. However

researcharxiv-cs-ro

GeGS-PCR: Effective and Robust 3D Point Cloud Registration with Two-Stage Color-Enhanced Geometric-3DGS Fusion

arXiv:2604.17721v1 Announce Type: new Abstract: We address the challenge of point cloud registration using color information, where traditional methods relying solely on geometric features often strug

Geometry-Guided 3D Visual Token Pruning for Video-Language Models

arXiv:2604.18260v1 Announce Type: new Abstract: Multimodal large language models have demonstrated remarkable capabilities in 2D vision, motivating their extension to 3D scene understanding. Recent st