research

Using ASP(Q) to Handle Inconsistent Prioritized Data

arXiv:2604.21603v1 Announce Type: cross Abstract: We explore the use of answer set programming (ASP) and its extension with quantifiers, ASP(Q), for inconsistency-tolerant querying of prioritized data

Validating a Deep Learning Algorithm to Identify Patients with Glaucoma using Systemic Electronic Health Records

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arXiv:2604.20921v1 Announce Type: new Abstract: We evaluated whether a glaucoma risk assessment (GRA) model trained on All of Us national data can identify patients at high probability of glaucoma usi

researcharxiv-cs-lg

24 Apr 2026

Verifying Machine Learning Interpretability Requirements through Provenance

arXiv:2604.21599v1 Announce Type: cross Abstract: Machine Learning (ML) Engineering is a growing field that necessitates an increase in the rigor of ML development. It draws many ideas from software e

VVS: Accelerating Speculative Decoding for Visual Autoregressive Generation via Partial Verification Skipping

arXiv:2511.13587v2 Announce Type: replace-cross Abstract: Visual autoregressive (AR) generation models have demonstrated strong potential for image generation, yet their next-token-prediction paradigm

Watts-per-Intelligence Part II: Algorithmic Catalysis

arXiv:2604.20897v1 Announce Type: cross Abstract: We develop a thermodynamic theory of algorithmic catalysis within the watts-per-intelligence framework, identifying reusable computational structures

Weighted quantization using MMD: From mean field to mean shift via gradient flows

arXiv:2502.10600v4 Announce Type: replace-cross Abstract: Approximating a probability distribution using a set of particles is a fundamental problem in machine learning and statistics, with applicatio

Weighting What Matters: Boosting Sample Efficiency in Medical Report Generation via Token Reweighting

arXiv:2604.21082v1 Announce Type: new Abstract: Training vision-language models (VLMs) for medical report generation is often hindered by the scarcity of high-quality annotated data. This work evaluat

Words that make SENSE: Sensorimotor Norms in Learned Lexical Token Representations

arXiv:2602.00469v2 Announce Type: replace-cross Abstract: While word embeddings derive meaning from co-occurrence patterns, human language understanding is grounded in sensory and motor experience. We

ZipFold: Modular Actuators for Scaleable Adaptive Robots

arXiv:2604.05260v2 Announce Type: replace Abstract: There is a growing need for robots that can change their shape, size and mechanical properties to adapt to evolving tasks and environments. However,

researcharxiv-cs-ro

3D Smoke Scene Reconstruction Guided by Vision Priors from Multimodal Large Language Models

arXiv:2604.05687v2 Announce Type: replace Abstract: Reconstructing 3D scenes from smoke-degraded multi-view images is particularly difficult because smoke introduces strong scattering effects, view-de

A Computational Model of Message Sensation Value in Short Video Multimodal Features that Predicts Sensory and Behavioral Engagement

arXiv:2604.19995v1 Announce Type: new Abstract: The contemporary media landscape is characterized by sensational short videos. While prior research examines the effects of individual multimodal featur

A Kinematic Framework for Evaluating Pinch Configurations in Robotic Hand Design without Object or Contact Models

arXiv:2604.20692v1 Announce Type: new Abstract: Evaluating the pinch capability of a robotic hand is important for understanding its functional dexterity. However, many existing grasp evaluation metho

researcharxiv-cs-ro

A new AI model for probing fusion plasma behavior

IBM Research has developed an AI model designed to analyze and predict the behavior of fusion plasma, advancing computational capabilities for nuclear fusion research. The model likely leverages machi

researchibm-research

A novel attention mechanism for noise-adaptive and robust segmentation of microtubules in microscopy images

arXiv:2507.07800v3 Announce Type: replace-cross Abstract: Segmenting cytoskeletal filaments in microscopy images is essential for studying their roles in cellular processes. However, this task is high

Accumulated Aggregated D-Optimal Designs for Estimating Main Effects in Black-Box Models

arXiv:2510.08465v2 Announce Type: replace-cross Abstract: Estimating how individual input variables affect the output of a black-box model is a central task in explainable machine learning. However, e

ACT: Anti-Crosstalk Learning for Cross-Sectional Stock Ranking via Temporal Disentanglement and Structural Purification

arXiv:2604.20204v1 Announce Type: new Abstract: Cross-sectional stock ranking is a fundamental task in quantitative investment, relying on both temporal modeling of individual stocks and the capture o

Actually, AI already saves lives. In several countries, mammograms are examined by AI and radiologists. Reliability is improved. In the EU, …

Actually, AI already saves lives. In several countries, mammograms are examined by AI and radiologists. Reliability is improved. In the EU, every car sold must be equipped with Automatic Emergency Bra

researchyann-lecun--x

Adaptive Multi-task Learning for Multi-sector Portfolio Optimization

arXiv:2507.16433v2 Announce Type: replace-cross Abstract: Accurate transfer of information across multiple sectors to enhance model estimation is both significant and challenging in multi-sector portf

AFMRL: Attribute-Enhanced Fine-Grained Multi-Modal Representation Learning in E-commerce

arXiv:2604.20135v1 Announce Type: new Abstract: Multimodal representation is crucial for E-commerce tasks such as identical product retrieval. Large representation models (e.g., VLM2Vec) demonstrate s

Agnostic Language Identification and Generation

arXiv:2601.23258v2 Announce Type: replace-cross Abstract: Recent works on language identification and generation have established tight statistical rates at which these tasks can be achieved. These wo

ALAS: Adaptive Long-Horizon Action Synthesis via Async-pathway Stream Disentanglement

arXiv:2604.20721v1 Announce Type: new Abstract: Long-Horizon (LH) tasks in Human-Scene Interaction (HSI) are complex multi-step tasks that require continuous planning, sequential decision-making, and

researcharxiv-cs-ro

Algorithm Selection with Zero Domain Knowledge via Text Embeddings

arXiv:2604.19753v1 Announce Type: new Abstract: We propose a feature-free approach to algorithm selection that replaces hand-crafted instance features with pretrained text embeddings. Our method, Zero

Aligning Stuttered-Speech Research with End-User Needs: Scoping Review, Survey, and Guidelines

arXiv:2604.20535v1 Announce Type: new Abstract: Atypical speech is receiving greater attention in speech technology research, but much of this work unfolds with limited interdisciplinary dialogue. For

Analysis of Nystrom method with sequential ridge leverage scores

arXiv:2604.20077v1 Announce Type: new Abstract: Large-scale kernel ridge regression (KRR) is limited by the need to store a large kernel matrix K_t. To avoid storing the entire matrix K_t, Nystrom met

Analyzing Shapley Additive Explanations to Understand Anomaly Detection Algorithm Behaviors and Their Complementarity

arXiv:2602.00208v2 Announce Type: replace-cross Abstract: Unsupervised anomaly detection is a challenging problem due to the diversity of data distributions and the lack of labels. Ensemble methods ar

AnatomicalNets: A Multi-Structure Segmentation and Contour-Based Distance Estimation Pipeline for Clinically Grounded Lung Cancer T-Staging

arXiv:2511.19367v2 Announce Type: replace-cross Abstract: Accurate tumor staging in lung cancer is crucial for prognosis and treatment planning and is governed by explicit anatomical criteria under fi

AROMA: Augmented Reasoning Over a Multimodal Architecture for Virtual Cell Genetic Perturbation Modeling

arXiv:2604.20263v1 Announce Type: cross Abstract: Virtual cell modeling predicts molecular state changes under genetic perturbations in silico, which is essential for biological mechanism studies. How

Auto-Unrolled Proximal Gradient Descent: An AutoML Approach to Interpretable Waveform Optimization

arXiv:2603.17478v2 Announce Type: replace-cross Abstract: This study explores the combination of automated machine learning (AutoML) with model-based deep unfolding (DU) for optimizing wireless beamfo

AutoGraphAD: Unsupervised network anomaly detection using Variational Graph Autoencoders

arXiv:2511.17113v2 Announce Type: replace-cross Abstract: Network Intrusion Detection Systems (NIDS) are essential tools for detecting network attacks and intrusions. While extensive research has expl

Automated Description Generation of Cytologic Findings for Lung Cytological Images Using a Pretrained Vision Model and Dual Text Decoders: Preliminary Study

arXiv:2403.18151v2 Announce Type: replace-cross Abstract: Objective: Cytology plays a crucial role in lung cancer diagnosis. Pulmonary cytology involves cell morphological characterization in the spec

Believing without Seeing: Quality Scores for Contextualizing Vision-Language Model Explanations

arXiv:2509.25844v3 Announce Type: replace Abstract: When people query Vision-Language Models (VLMs) but cannot see the accompanying visual context (e.g. for blind and low-vision users), augmenting VLM

Beyond ZOH: Advanced Discretization Strategies for Vision Mamba

arXiv:2604.20606v1 Announce Type: cross Abstract: Vision Mamba, as a state space model (SSM), employs a zero-order hold (ZOH) discretization, which assumes that input signals remain constant between s

BIG PERSONAL UPDATE. I've joined a16z as a partner investing in infra and AI. I'm also stepping down as CEO of Rosebud AI. I reflect in this…

BIG PERSONAL UPDATE. I've joined a16z as a partner investing in infra and AI. I'm also stepping down as CEO of Rosebud AI. I reflect in this article on my 8 years of building in generative AI. At @a16

researchdavid-ha--x

Bio-inspired Color Constancy: From Gray Anchoring Theory to Gray Pixel Methods

arXiv:2604.20243v1 Announce Type: new Abstract: Color constancy is a fundamental ability of many biological visual systems and a crucial step in computer imaging systems. Bio-inspired modeling offers

Build your own harness, folks. You won't regret it. These days, you just have to fix things yourself. It's doable, and it will set you up to…

Build your own harness, folks. You won't regret it. These days, you just have to fix things yourself. It's doable, and it will set you up to easily deal with some of the madness that's happening in th

researchdair-ai--x

Calibrating conditional risk

arXiv:2604.20409v1 Announce Type: new Abstract: We introduce and study the problem of calibrating conditional risk, which involves estimating the expected loss of a prediction model conditional on inp

Caught in the Web of Words: Do LLMs Fall for Spin in Medical Literature?

arXiv:2502.07963v4 Announce Type: replace-cross Abstract: Medical research faces well-documented challenges in translating novel treatments into clinical practice. Publishing incentives encourage rese

Causal-Transformer with Adaptive Mutation-Locking for Early Prediction of Acute Kidney Injury

arXiv:2604.20259v1 Announce Type: new Abstract: Accurate early prediction of Acute Kidney Injury (AKI) is critical for timely clinical intervention. However, existing deep learning models struggle wit

Centering Ecological Goals in Automated Identification of Individual Animals

arXiv:2604.20626v1 Announce Type: cross Abstract: Recognizing individual animals over time is central to many ecological and conservation questions, including estimating abundance, survival, movement,

Co-Located Tests, Better AI Code: How Test Syntax Structure Affects Foundation Model Code Generation

arXiv:2604.19826v1 Announce Type: cross Abstract: AI coding assistants increasingly generate code alongside tests. How developers structure test code, whether inline with the implementation or in sepa

CoAuthorAI: A Human in the Loop System For Scientific Book Writing

arXiv:2604.19772v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used in scientific writing but struggle with book-length tasks, often producing inconsistent structure a

Cold-Start Forecasting of New Product Life-Cycles via Conditional Diffusion Models

arXiv:2604.20370v1 Announce Type: new Abstract: Forecasting the life-cycle trajectory of a newly launched product is important for launch planning, resource allocation, and early risk assessment. This

Commonsense Knowledge with Negation: A Resource to Enhance Negation Understanding

arXiv:2604.19921v1 Announce Type: new Abstract: Negation is a common and important semantic feature in natural language, yet Large Language Models (LLMs) struggle when negation is involved in natural

Composition-RL: Compose Your Verifiable Prompts for Reinforcement Learning of Large Language Models

arXiv:2602.12036v2 Announce Type: replace Abstract: Large-scale verifiable prompts underpin the success of Reinforcement Learning with Verifiable Rewards (RLVR), but they contain many uninformative ex

Computing the Reachability Value of Posterior-Deterministic POMDPs

arXiv:2602.07473v2 Announce Type: replace Abstract: Partially observable Markov decision processes (POMDPs) are a fundamental model for sequential decision-making under uncertainty. However, many veri

Concept Graph Convolutions: Message Passing in the Concept Space

arXiv:2604.20082v1 Announce Type: new Abstract: The trust in the predictions of Graph Neural Networks is limited by their opaque reasoning process. Prior methods have tried to explain graph networks v

Confidence-Based Mesh Extraction from 3D Gaussians

arXiv:2603.24725v2 Announce Type: replace Abstract: Recently, 3D Gaussian Splatting (3DGS) greatly accelerated mesh extraction from posed images due to its explicit representation and fast software ra

Construction of a Battery Research Knowledge Graph using a Global Open Catalog

arXiv:2604.20241v1 Announce Type: new Abstract: Battery research is a rapidly growing and highly interdisciplinary field, making it increasingly difficult to track relevant expertise and identify pote