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arXiv:2604.17543v1 Announce Type: new Abstract: Large language models (LLMs) have achieved remarkable success in general-domain tasks, yet their direct application to the legal domain remains challeng

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Applications

RA-RRG: Multimodal Retrieval-Augmented Radiology Report Generation with Key Phrase Extraction

DGX agent

arXiv:2504.07415v2 Announce Type: replace-cross Abstract: Automated radiology report generation (RRG) holds potential to reduce the workload of radiologists, and recent advances in multimodal large la

applicationsarxiv-cs-cl

21 Apr 2026

Tutorials

Self-Reinforcing Controllable Synthesis of Rare Relational Data via Bayesian Calibration

arXiv:2604.16817v1 Announce Type: new Abstract: Imbalanced data is commonly present in real-world applications. While data synthesis can effectively mitigate the data scarcity problem of rare-classes,

tutorialsarxiv-cs-lg

SFTMix: Elevating Language Model Instruction Tuning with Mixup Recipe

arXiv:2410.05248v4 Announce Type: replace Abstract: To acquire instruction-following capabilities, large language models (LLMs) undergo instruction tuning, where they are trained on instruction-respon

Textual Bayes: Quantifying Prompt Uncertainty in LLM-Based Systems

arXiv:2506.10060v2 Announce Type: replace Abstract: Although large language models (LLMs) are becoming increasingly capable of solving challenging real-world tasks, accurately quantifying their uncert

The Breakthrough of Sleep: A Contactless Approach for Accurate Sleep Stage Detection Using the Sleepal AI Lamp

arXiv:2604.16442v1 Announce Type: cross Abstract: Sleep staging is essential for the assessment of sleep quality and the diagnosis of sleep-related disorders. Conventional polysomnography (PSG), while

Thermal-GEMs: Generalized Models for Building Thermal Dynamics

arXiv:2604.16443v1 Announce Type: cross Abstract: Data-driven models for building thermal dynamics are a scalable approach for enabling energy-efficient operation through fault detection & diagnosis o

Topology-Preserving Scalar Field Optimization for Boundary-Conforming Spiral Toolpaths on Multiply Connected Freeform Surfaces

arXiv:2512.22502v2 Announce Type: replace Abstract: Ball-end milling path planning on multiply connected freeform surfaces is pivotal for high-quality and efficient machining of components in automoti

AeroDeshadow: Physics-Guided Shadow Synthesis and Penumbra-Aware Deshadowing for Aerospace Imagery

arXiv:2604.15903v1 Announce Type: new Abstract: Shadows are prevalent in high-resolution aerospace imagery (ASI). They often cause spectral distortion and information loss, which degrade downstream in

AHS: Adaptive Head Synthesis via Synthetic Data Augmentations

arXiv:2604.15857v1 Announce Type: new Abstract: Recent digital media advancements have created increasing demands for sophisticated portrait manipulation techniques, particularly head swapping, where

Foundation Models in Robotics: A Comprehensive Review of Methods, Models, Datasets, Challenges and Future Research Directions

arXiv:2604.15395v1 Announce Type: new Abstract: Over the recent years, the field of robotics has been undergoing a transformative paradigm shift from fixed, single-task, domain-specific solutions towa

Modern Structure-Aware Simplicial Spatiotemporal Neural Network

arXiv:2604.15833v1 Announce Type: new Abstract: Spatiotemporal modeling has evolved beyond simple time series analysis to become fundamental in structural time series analysis. While current research

That chances of a 1/n event happening in n tries converges quickly on 63% (1-1/e to be exact) has been one of my favorite useful real world …

This post discusses the mathematical principle that when attempting a 1/n probability event n times, the probability of at least one success converges to approximately 63.2% (mathematically 1 - 1/e ≈

applicationsswyx--x

19 Apr 2026

Bayesian Optimization with Gaussian Processes to Accelerate Stationary Point Searches

arXiv:2603.10992v3 Announce Type: replace-cross Abstract: Building local surrogates to accelerate stationary point searches on potential energy surfaces spans decades of effort. Done correctly, surrog

HARNESS: Lightweight Distilled Arabic Speech Foundation Models

arXiv:2604.14186v1 Announce Type: cross Abstract: Large self-supervised speech (SSL) models achieve strong downstream performance, but their size limits deployment in resource-constrained settings. We

IUQ: Interrogative Uncertainty Quantification for Long-Form Large Language Model Generation

arXiv:2604.15109v1 Announce Type: new Abstract: Despite the rapid advancement of Large Language Models (LLMs), uncertainty quantification in LLM generation is a persistent challenge. Although recent a

Material-Agnostic Zero-Shot Thermal Inference for Metal Additive Manufacturing via a Parametric PINN Framework

arXiv:2604.14562v1 Announce Type: new Abstract: Accurate thermal modeling in metal additive manufacturing (AM) is essential for understanding the process-structure-performance relationship. While prio

OmniLight: One Model to Rule All Lighting Conditions

arXiv:2604.15170v1 Announce Type: new Abstract: Adverse lighting conditions, such as cast shadows and irregular illumination, pose significant challenges to computer vision systems by degrading visibi

Quality-Aware Calibration for AI-Generated Image Detection in the Wild

arXiv:2604.15027v1 Announce Type: new Abstract: Significant progress has been made in detecting synthetic images, however most existing approaches operate on a single image instance and overlook a key

Text2Arch: A Dataset for Generating Scientific Architecture Diagrams from Natural Language Descriptions

arXiv:2604.14941v1 Announce Type: new Abstract: Communicating complex system designs or scientific processes through text alone is inefficient and prone to ambiguity. A system that automatically gener

Variance Computation for Weighted Model Counting with Knowledge Compilation Approach

arXiv:2601.03523v2 Announce Type: replace Abstract: One of the most important queries in knowledge compilation is weighted model counting (WMC), which has been applied to probabilistic inference on va

Research

A Multi-Stage Optimization Pipeline for Bethesda Cell Detection in Pap Smear Cytology

arXiv:2604.13939v1 Announce Type: new Abstract: Computer vision techniques have advanced significantly in recent years, finding diverse and impactful applications within the medical field. In this pap

researcharxiv-cs-cv

Abstract 3D Perception for Spatial Intelligence in Vision-Language Models

arXiv:2511.10946v3 Announce Type: replace Abstract: Vision-language models (VLMs) struggle with 3D-related tasks such as spatial cognition and physical understanding, which are crucial for real-world

Building with Databricks Document Intelligence and Lakeflow

Databricks Document Intelligence and Lakeflow are tools designed to extract structured data from unstructured documents using AI and machine learning capabilities. This resource covers how to build an

applicationsdatabricks

Feed-Forward 3D Scene Modeling: A Problem-Driven Perspective

arXiv:2604.14025v1 Announce Type: new Abstract: Reconstructing 3D representations from 2D inputs is a fundamental task in computer vision and graphics, serving as a cornerstone for understanding and i

How IBM Quantum is enabling healthcare and biology research

IBM Quantum is leveraging quantum computing technology to advance healthcare and biology research, with the company highlighting selected finalists in their quantum-for-biology (Q4Bio) initiative. The

applicationsibm-research

IWLV-Ramayana: A Sarga-Aligned Parallel Corpus of Valmiki's Ramayana Across Indian Languages

arXiv:2604.13078v1 Announce Type: new Abstract: The Ramayana is among the most influential literary traditions of South and Southeast Asia, transmitted across numerous linguistic and cultural contexts

Random Walk Learning and the Pac-Man Attack

arXiv:2508.05663v4 Announce Type: replace-cross Abstract: Random walk (RW)-based algorithms have long been popular in distributed systems due to low overheads and scalability, with recent growing appl

Spectral Thompson sampling

arXiv:2604.13739v1 Announce Type: new Abstract: Thompson Sampling (TS) has attracted a lot of interest due to its good empirical performance, in particular in the computational advertising. Though suc

Characterizing Human Semantic Navigation in Concept Production as Trajectories in Embedding Space

arXiv:2602.05971v2 Announce Type: replace Abstract: Semantic representations can be framed as a structured, dynamic knowledge space through which humans navigate to retrieve and manipulate meaning. To

Research

How much harder is it these days to get into a PhD program without having a high ranking degree for UG? [D]

researchr-machinelearning

This Reddit discussion thread from r/MachineLearning explores the growing challenges faced by applicants from non-elite undergraduate institutions when applying to PhD programs in machine learning and

INTARG: Informed Real-Time Adversarial Attack Generation for Time-Series Regression

arXiv:2604.11928v1 Announce Type: new Abstract: Time-series forecasting aims to predict future values by modeling temporal dependencies in historical observations. It is a critical component of many r

On Efficient Variants of Segment Anything Model: A Survey

arXiv:2410.04960v5 Announce Type: replace Abstract: The Segment Anything Model (SAM) is a foundational model for image segmentation tasks, known for its strong generalization across diverse applicatio

On the Geometry of Receiver Operating Characteristic and Precision-Recall Curves

arXiv:2504.02169v3 Announce Type: replace-cross Abstract: We study the geometry of Receiver Operating Characteristic (ROC) and Precision-Recall (PR) curves in binary classification problems. The key f

RegD: Hierarchical Embeddings via Dissimilarity between Arbitrary Euclidean Regions

arXiv:2501.17518v3 Announce Type: replace-cross Abstract: Hierarchical data is common in many domains like life sciences and e-commerce, and its embeddings often play a critical role. While hyperbolic

Rethinking Satellite Image Restoration for Onboard AI: A Lightweight Learning-Based Approach

arXiv:2604.12807v1 Announce Type: cross Abstract: Satellite image restoration aims to improve image quality by compensating for degradations (e.g., noise and blur) introduced by the imaging system and

SmellNet: A Large-scale Dataset for Real-world Smell Recognition

arXiv:2506.00239v5 Announce Type: replace Abstract: The ability of AI to sense and identify various substances based on their smell alone can have profound impacts on allergen detection (e.g. smelling

SpecBranch: Speculative Decoding via Hybrid Drafting and Rollback-Aware Branch Parallelism

arXiv:2506.01979v4 Announce Type: replace-cross Abstract: Recently, speculative decoding (SD) has emerged as a promising technique to accelerate LLM inference by employing a small draft model to propo

Can Textual Reasoning Improve the Performance of MLLMs on Fine-grained Visual Classification?

arXiv:2601.06993v2 Announce Type: replace Abstract: Multi-modal large language models (MLLMs) exhibit strong general-purpose capabilities, yet still struggle on Fine-Grained Visual Classification (FGV

CraftGraffiti: Exploring Human Identity with Custom Graffiti Art via Facial-Preserving Diffusion Models

arXiv:2508.20640v2 Announce Type: replace Abstract: Preserving facial identity under extreme stylistic transformation remains a major challenge in generative art. In graffiti, a high-contrast, abstrac

Model Releases

Decompose, Mix, Adapt: A Unified Framework for Parameter-Efficient Neural Network Recombination and Compression

model-releasesarxiv-cs-cv

arXiv:2603.27383v2 Announce Type: replace Abstract: Parameter Recombination (PR) methods aim to efficiently compose the weights of a neural network for applications like Parameter-Efficient FineTuning

Diffusion Reinforcement Learning Based Online 3D Bin Packing Spatial Strategy Optimization

arXiv:2604.10953v1 Announce Type: new Abstract: The online 3D bin packing problem is important in logistics, warehousing and intelligent manufacturing, with solutions shifting to deep reinforcement le

Inferring World Belief States in Dynamic Real-World Environments

arXiv:2604.11020v1 Announce Type: new Abstract: We investigate estimating a human's world belief state using a robot's observations in a dynamic, 3D, and partially observable environment. The methods

Interactive Interface For Semantic Segmentation Dataset Synthesis

arXiv:2506.23470v2 Announce Type: replace Abstract: The rapid advancement of AI and computer vision has significantly increased the demand for high-quality annotated datasets, particularly for semanti

Safety

Multi-Model Synthetic Training for Mission-Critical Small Language Models

arXiv:2509.13047v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have demonstrated remarkable capabilities across many domains, yet their application to specialized fields remain

safetyarxiv-cs-ai

Agents

NimbusGuard: A Novel Framework for Proactive Kubernetes Autoscaling Using Deep Q-Networks

arXiv:2604.11017v1 Announce Type: cross Abstract: Cloud native architecture is about building and running scalable microservice applications to take full advantage of the cloud environments. Managed K

agentsarxiv-cs-ai

Ninja Codes: Neurally Generated Fiducial Markers for Stealthy 6-DoF Tracking

arXiv:2510.18976v2 Announce Type: replace Abstract: In this paper we describe Ninja Codes, neurally generated fiducial markers that can be made to naturally blend into various real-world environments.

NTIRE 2026 Challenge on Single Image Reflection Removal in the Wild: Datasets, Results, and Methods

arXiv:2604.10321v1 Announce Type: new Abstract: In this paper, we review the NTIRE 2026 challenge on single-image reflection removal (SIRR) in the Wild. SIRR is a fundamental task in image restoration