Search: “research”

Can I Have Your Order? Monte-Carlo Tree Search for Slot Filling Ordering in Diffusion Language Models

arXiv:2602.12586v2 Announce Type: replace Abstract: While plan-and-infill decoding in Masked Diffusion Models (MDMs) shows promise for mathematical and code reasoning, performance remains highly sensi

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Research

Can LLMs Use Linguistic Uncertainty Markers to Reliably Reflect Intrinsic Confidence?

DGX agent

arXiv:2605.28778v1 Announce Type: new Abstract: LLMs' linguistically expressed confidence should faithfully reflect their intrinsic uncertainty. While recent work shows LLMs struggle to use epistemic

researcharxiv-cs-cl

28 May 2026

Can Quantum Federated Learning Withstand Circuit-Level Backdoors?

arXiv:2605.27416v1 Announce Type: cross Abstract: Quantum Federated Learning (QFL) inherits the core vulnerability of federated optimization to malicious clients, while also introducing an attack surf

Challenges in Explaining Pretrained Clinical Text Classifiers

arXiv:2605.28060v1 Announce Type: new Abstract: Explaining the predictions of neural models in clinical NLP remains a significant challenge, especially for complex tasks involving long, unstructured m

Chreode: A Cell World Model for One-Step Temporal Dynamics and Perturbation Prediction

arXiv:2605.28111v1 Announce Type: new Abstract: Predicting how a cell will change its transcriptional state under a developmental signal or a genetic perturbation is the computational core of in-silic

Clark Hash: Stateless Sparse Johnson-Lindenstrauss Quantization for Neural Embeddings

arXiv:2605.28034v1 Announce Type: new Abstract: Clark Hash is a small method for storing neural embeddings in less space. It normalizes each database vector, applies a deterministic sparse signed John

Clinical Validation of the Melanoscope AI Mobile Dermoscopy Clinical Decision Support System

arXiv:2605.27561v1 Announce Type: cross Abstract: Introduction. Early detection of malignant skin lesions is critical for prognosis, yet dermatologist shortages in Russian regions limit screening cove

ClothTransformer: Unified Latent-Space Transformers for Scalable Cloth Simulation

arXiv:2605.27852v1 Announce Type: cross Abstract: Unified and scalable Transformers have recently achieved remarkable success in modeling diverse phenomena traditionally associated with computer graph

Comonadic Morphophonology: A Compositional Framework for Context-Dependent Morphological Rules in Finnish

arXiv:2605.28484v1 Announce Type: new Abstract: Composing finite-state transducers (FSTs) for context-dependent morphophonological rules -- consonant gradation, vowel harmony, possessive suffix assimi

Compositional Generalization in Autoregressive Models via Logit Composition

arXiv:2605.28304v1 Announce Type: new Abstract: Composing autoregressive models remains a core challenge in understanding how large language models can combine behaviors or skills learned across tasks

Conditionally Site-Independent Neural Evolution of Antibody Sequences

arXiv:2602.18982v4 Announce Type: replace Abstract: Common deep learning approaches for antibody engineering focus on modeling the marginal distribution of sequences. By treating sequences as independ

Conformal Prediction for Hierarchical Data

arXiv:2411.13479v4 Announce Type: replace-cross Abstract: We consider conformal prediction for multivariate data and focus on hierarchical data, where some components are linear combinations of others

Constrained Auto-Bidding via Generative Response Modeling

arXiv:2605.27811v1 Announce Type: new Abstract: Auto-bidding systems aim to maximize advertiser value over long horizons under budget constraints and ratio targets such as cost-per-acquisition, yet fu

Continual Learning in Modern Hopfield Networks with an Application to Diffusion Models

arXiv:2605.27975v1 Announce Type: new Abstract: Generative models, including diffusion models, are increasingly used as foundation models and adapted through sequential fine-tuning, making continual l

CORE: Contrastive Reflection Enables Rapid Improvements in Reasoning

arXiv:2605.28742v1 Announce Type: new Abstract: Language models can use verifiable rewards to improve at a wide variety of reasoning tasks. However, both parametric (e.g. RLVR) and non-parametric (e.g

Cross-Modal Action Recognition in Egocentric Video Using Mamba: Integrating RGB and Hand Skeleton Streams via CLS Token Fusion Strategies

arXiv:2605.24302v2 Announce Type: replace Abstract: Egocentric action recognition is a challenging task due to erratic camera motion, frequent hand occlusion, and the difficulty of maintaining consist

CubePart: An Open-Vocabulary Part-Controllable 3D Generator

arXiv:2605.28763v1 Announce Type: new Abstract: Interactive 3D assets used in games and simulation are typically decomposed into specific semantic parts to support animation, physics, and scripted beh

CuriosAI Submission to the CASTLE Challenge at EgoVis 2026

arXiv:2605.27800v1 Announce Type: new Abstract: CASTLE 2026 asks 185 multiple-choice questions over 600+ hours of synchronized multi-view egocentric video. We explore two approaches on top of a shared

DAISI: Data Assimilation with Inverse Sampling using Stochastic Interpolants

arXiv:2512.00252v4 Announce Type: replace-cross Abstract: Data assimilation (DA) is a cornerstone of scientific and engineering applications, combining model forecasts with sparse and noisy observatio

Debate Helps Weak Judges Reward Stronger Models

arXiv:2605.27483v1 Announce Type: cross Abstract: Despite theoretical promise, debate as a scalable oversight protocol has produced mixed empirical results: gains in some settings, and null effects in

Decoupling Variance and Scale-Invariant Updates in Adaptive Gradient Descent for Unified Vector and Matrix Optimization

arXiv:2602.06880v2 Announce Type: replace Abstract: Adaptive methods like Adam have become the extit{de facto} standard for large-scale vector and Euclidean optimization due to their coordinate-wise a

Deep Learning Strain Estimation: Is Physics-Based Simulation the Solution?

arXiv:2605.28697v1 Announce Type: cross Abstract: Speckle tracking echocardiography (STE) is the clinical standard for myocardial strain estimation. Despite good performance on global strain (GLS), it

Deep Neural Network Training as Random Effects: An Optimization-Inference Duality

arXiv:2605.27991v1 Announce Type: cross Abstract: Deep neural networks (DNNs) have achieved remarkable empirical success, yet their training dynamics remain understood mainly from optimization rather

Density-aware Sample-specific Attack

arXiv:2605.27809v1 Announce Type: new Abstract: Despite recent progress in backdoor attacks, existing methods remain susceptible to post-training defenses that erase the backdoor through fine-tuning o

Design of a Real-time Asynchronous Monocular Odometry for Planetary Exploration

arXiv:2605.27661v1 Announce Type: new Abstract: We describe our preliminary design of a real-time asynchronous event-based monocular odometry for planetary exploration. Operating under strict computat

researcharxiv-cs-ro

Detecting Diffusion-Generated Time Series Under Generator Shift

arXiv:2605.28355v1 Announce Type: new Abstract: The boundary between real and diffusion-generated time series is becoming increasingly difficult to draw, yet detection in this domain remains underexpl

Developing an Intelligent Job Recommendation System Using Semantic Retrieval and Explainable AI Techniques

arXiv:2605.27656v1 Announce Type: cross Abstract: Online recruitment platforms require recommendation methods capable of retrieving relevant job opportunities from large and heterogeneous collections

DODO: Discrete OCR Diffusion Models

arXiv:2602.16872v2 Announce Type: replace Abstract: Optical Character Recognition (OCR) is a fundamental task for digitizing information, serving as a critical bridge between visual data and textual u

Domain size asymptotics for Markov logic networks

arXiv:2509.04192v2 Announce Type: replace Abstract: A Markov logic network (MLN) M determines a probability distribution P_n^M on the set mathbf{W}_n of structures, or ``possible worlds'', with domain

Dynamic Topic Modeling with a Higher-Order Hypergraphical Representation

arXiv:2605.28269v1 Announce Type: new Abstract: Dynamic topic modeling is widely used to analyze evolving trends in scientific literature, medical records, and social media. Traditional topic models r

EAGer: Entropy-Aware GEneRation for Adaptive Inference-Time Scaling

arXiv:2510.11170v2 Announce Type: replace-cross Abstract: With the rise of reasoning language models and test-time scaling methods as a paradigm for improving model performance, substantial computatio

EchoAvatar: Real-time Generative Avatar Animation from Audio Streams

arXiv:2605.28272v1 Announce Type: new Abstract: Real-time synthesis of high-fidelity 3D character motion from audio is a pivotal component for next-generation interactive avatars and virtual assistant

Efficient Post-training of LLMs for Code Generation With Offline Reinforcement Learning

arXiv:2605.28409v1 Announce Type: new Abstract: Post-training using online reinforcement learning (RL) is an important training step for LLMs, including code-generating models. However, online RL for

EgoRelight: Egocentric Human Capture and Illumination Recovery for Relightable and Photoreal Avatar Rendering

arXiv:2605.28401v1 Announce Type: new Abstract: Mixed Reality (MR) headsets promise a future of immersive telepresence where virtual humans blend indistinguishably into real or virtual surroundings. A

EIT-Pneumatic Hybrid Robotic Skin for Practical and Accurate Force Map Reconstruction

arXiv:2605.28468v1 Announce Type: new Abstract: We present a hybrid robotic skin that combines electrical impedance tomography (EIT) with pneumatic tactile sensing to improve force reconstruction capa

researcharxiv-cs-ro

Enhancing Ultra-low-field MRI with Segmentation-guided Adversarial Learning

arXiv:2605.28016v1 Announce Type: new Abstract: Ultra-low-field (ULF) MRI offers portable and low-cost imaging but suffers from poor image quality. To address this, we present our submission to the 20

Entropy-aware Masking for Masked Language Modeling

arXiv:2605.28526v1 Announce Type: new Abstract: Masked language modeling has become a standard pretraining objective for training encoder-based language models. In this approach, certain tokens in the

Entropy Distribution as a Fingerprint for Hallucinations in Generative Models

arXiv:2605.28264v1 Announce Type: new Abstract: Large Language Models (LLMs) often generate factually incorrect outputs, commonly termed hallucinations, that undermine trust and limit deployment in hi

Evaluating the Feasibility of Inferring Dietary Behavior Change Receptivity from Egocentric Images of Eating Environment

arXiv:2605.27950v1 Announce Type: new Abstract: Accurately assessing dietary behavior change receptivity is essential for designing effective just-in-time adaptive interventions (JITAIs) that promote

Evaluating the Generation Capabilities of Large Chinese Language Models

arXiv:2308.04823v5 Announce Type: replace Abstract: This paper unveils CG-Eval, the first-ever comprehensive and automated evaluation framework designed for assessing the generative capabilities of la

Event-based Motion & Appearance Fusion for 6D Object Pose Tracking

arXiv:2603.08264v2 Announce Type: replace Abstract: Object pose tracking is a fundamental and essential task for robotics to perform tasks in the home and industrial settings. The most commonly used s

Excited Pfaffians: Generalized Neural Wave Functions Across Structure and State

arXiv:2603.14515v2 Announce Type: replace Abstract: Neural-network wave functions in Variational Monte Carlo (VMC) have achieved great success in accurately representing both ground and excited states

Explaining Digital Pathology Models via Clustering Activations

arXiv:2511.14558v2 Announce Type: replace Abstract: We present a clustering-based explainability technique for digital pathology models based on convolutional neural networks. Unlike commonly used met

Explaining is Harder Than Predicting Alone: Evaluating Concept-based Explanations of MLLMs as ICL Visual Classifiers

arXiv:2605.28215v1 Announce Type: new Abstract: In-context learning (ICL) enables multimodal large language models (MLLMs) to classify images from a few labelled examples. Yet, how these models use th

Explanation Generation for Contradiction Reconciliation with LLMs

arXiv:2603.22735v2 Announce Type: replace Abstract: Existing NLP work commonly treats contradictions as errors to be resolved by choosing which statements to accept or discard. Yet a key aspect of hum

Explicit Critic Guidance for Aligning Diffusion Models

arXiv:2605.27736v1 Announce Type: cross Abstract: Online reinforcement learning is becoming increasingly important for aligning diffusion models with non-differentiable objectives. However, existing m

Expressive Power of Floating-Point Neural Networks with Arbitrary Reduction Orders and Inexact Activation Implementations

arXiv:2605.28704v1 Announce Type: new Abstract: Most existing expressivity theories for neural networks assume exact real arithmetic, whereas practical neural networks are executed under finite-precis

Extensions of Robbins-Siegmund Theorem with Applications in Reinforcement Learning

arXiv:2509.26442v2 Announce Type: replace Abstract: The Robbins-Siegmund theorem establishes the convergence of stochastic processes that are almost supermartingales and is one of the most commonly us