Search: “framework”

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning

arXiv:2505.11758v2 Announce Type: replace-cross Abstract: Few-shot adaptation of vision-language models remains fundamentally limited by how negative class signals are handled at inference. Existing m

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Generating Legal Commentaries from Case Databases via Retrieval, Clustering, and Generation

DGX agent

arXiv:2605.24534v1 Announce Type: new Abstract: We present a fully automated pipeline that transforms large collections of court decisions into legal commentaries for statutes - without providing any

applicationsarxiv-cs-cl

26 May 2026

Generative OOD-regularized Model-based Policy Optimization

arXiv:2605.24405v1 Announce Type: cross Abstract: We study sequential decision-making with offline reinforcement learning (RL). Traditional offline RL policies may result in out-of-distribution (OOD)

Local Ai

Generative Representation Learning on Hyper-relational Knowledge Graphs via Masked Discrete Diffusion

arXiv:2605.24064v1 Announce Type: cross Abstract: Hyper-relational knowledge graphs (HKGs) effectively represent complex facts. While inferring new knowledge in HKGs is a critical problem, current met

local-aiarxiv-cs-ai

Generative Visual Code Mobile World Models

arXiv:2602.01576v2 Announce Type: replace-cross Abstract: Mobile Graphical User Interface (GUI) World Models (WMs) offer a promising path for improving mobile GUI agent performance at train- and infer

GeoSVG-RL: Geometry-Aware Reinforcement Learning for Layout-Constrained Text-to-SVG Diagram Generation

arXiv:2605.25447v1 Announce Type: new Abstract: Generating structured, editable diagrams remains a significant challenge for contemporary large language models, despite their proficiency in general-pu

safetyarxiv-cs-cl

GlobalDentBench: A Multinational Benchmark for Evaluating LLM Clinical Reasoning in Dentistry with Expert Calibration

arXiv:2605.24636v1 Announce Type: new Abstract: While large language models (LLMs) hold transformative potential for medicine, their reasoning robustness and safety in real-world clinical scenarios re

Goal-driven Bayesian Optimal Experimental Design for Robust Decision-Making Under Model Uncertainty

arXiv:2605.26093v1 Announce Type: new Abstract: Bayesian optimal experimental design (BOED) selects experiments to maximize information gain about model parameters. However, in decision-critical setti

Agents

GRAIL: AI translation for scientists application workflow on satellite data

arXiv:2605.24784v1 Announce Type: new Abstract: Domain scientists increasingly develop Python scripts to analyze satellite imagery but they lack scalability to large-scale data. This paper demonstrate

agentsarxiv-cs-ai

GreenSeg: Ground Segmentation Algorithm for Agricultural Robots in Mediterranean Greenhouses using RGB-D Point Clouds

model-releasesarxiv-cs-ro

arXiv:2605.25279v1 Announce Type: new Abstract: Greenhouse agriculture in the Mediterranean region faces significant automation challenges due to its unique structural and environmental constraints. T

Grouter: Decoupling Routing from Representation for Accelerated MoE Training

arXiv:2603.06626v2 Announce Type: replace-cross Abstract: Traditional Mixture-of-Experts (MoE) training typically proceeds without any structural priors, effectively requiring the model to simultaneou

Grow-Prune-Freeze Networks: Adaptive & Continual Learning Technique for Olfactory Navigation

arXiv:2605.25170v1 Announce Type: cross Abstract: Training data for olfaction is scattered through disparate, non-standardized datasets that limit the ability to build representative world models. Olf

Growing a Neural Network in Breadth, Depth, and Time

arXiv:2605.25174v1 Announce Type: cross Abstract: Spatial and temporal resource constraints are critical for both biological and artificial intelligent systems. Here we define differentiable cost term

Guaranteeing Conservation of Integrals with Projection in Physics-Informed Neural Networks

arXiv:2511.09048v2 Announce Type: replace Abstract: We propose a novel projection method that guarantees the conservation of integral quantities in Physics-Informed Neural Networks (PINNs). While the

Guided Flow Matching for Forward and Inverse PDE Problems with Sparse Observations: Algorithm and Theory

arXiv:2605.25509v1 Announce Type: cross Abstract: Reconstructing PDE solutions from sparse observations is a core challenge in scientific computing. We present FM4PDE, a flow-matching generative frame

Hardware-Aware Federated Learning for Speech Emotion Recognition

arXiv:2605.24712v1 Announce Type: new Abstract: Federated learning (FL) enables privacy-preserving collaborative training across distributed edge devices, but real deployments involve heterogeneous cl

Local Ai

Hierarchical Local-Global Transformer for Temporal Sentence Grounding

arXiv:2208.14882v2 Announce Type: replace-cross Abstract: This paper studies the multimedia problem of temporal sentence grounding (TSG), which aims to accurately determine the specific video segment

local-aiarxiv-cs-cl

High-Risk AI Systems and the Problem of Identity in the European AI Act

arXiv:2605.23922v1 Announce Type: cross Abstract: The EU Artificial Intelligence Act (AIA) establishes a lifecycle governance regime for high-risk AI systems built around ex-ante conformity assessment

HiTeC: Hierarchical Contrastive Learning on Text-Attributed Hypergraph with Semantic-Aware Augmentation

arXiv:2508.03104v3 Announce Type: replace-cross Abstract: Contrastive learning (CL) has become a dominant paradigm for self-supervised hypergraph learning, enabling effective training without costly l

applicationsarxiv-cs-ai

HumanEgo: Zero-Shot Robot Learning from Minutes of Human Egocentric Videos

arXiv:2605.24934v1 Announce Type: cross Abstract: Human egocentric video captures rich manipulation demonstrations without any robot hardware, yet transferring these skills to robots remains challengi

Agents

HyLaT: Efficient Multi-Agent Communication via Hybrid Latent-Text Protocol

arXiv:2605.25421v1 Announce Type: new Abstract: Communication protocol design is a central challenge in large language model-based multi-agent systems. Existing single-channel approaches face an inher

agentsarxiv-cs-cl

Identifying and Mitigating Systemic Measurement Bias in Production LLM Inference Benchmarks

arXiv:2605.24217v1 Announce Type: new Abstract: As Large Language Models (LLMs) transition from research environments to production deployments, evaluating their performance against strict Service Lev

Implicit Null-space Manifold Generation for Redundant Robotic Systems

arXiv:2605.25770v1 Announce Type: new Abstract: Robotic systems with redundant degrees of freedom can achieve the same task outcome using multiple configurations, resulting in solution sets that form

researcharxiv-cs-ro

Improving Ensemble CAPE Forecasts with a Diffusion Model Incorporating Aerosol Information

arXiv:2605.24009v1 Announce Type: cross Abstract: Convective available potential energy (CAPE) is an important variable for forecasting severe weather and understanding deep convection and precipitati

safetyarxiv-cs-lg

Improving the Completeness and Comparability of Segment Disclosures: A Large Language Model Approach

arXiv:2605.23924v1 Announce Type: new Abstract: Segment-level disclosures are a central component of financial reporting, providing insight into firms' internal organization and the allocation of econ

safetyarxiv-cs-cl

Incentivized Exploration with Stochastic Covariates: A Two-Stage Mechanism Design for Recommender System

arXiv:2406.04374v2 Announce Type: replace-cross Abstract: Recommender systems play a crucial role in internet economies by connecting users with relevant products. However, designing effective recomme

Incorporating Deep Learning Design in Database Queries

arXiv:2605.24207v1 Announce Type: cross Abstract: Deep learning over relational databases is conventionally realized by translating data into graph representations and applying graph-based neural netw

Inference-Time Alignment of Diffusion Models via Trust-Region Iterative Twisted Sequential Monte Carlo

arXiv:2605.25123v1 Announce Type: cross Abstract: We study inference-time alignment for diffusion-based generative models, aiming to steer a base model toward high-reward outputs without updating its

INSIGHT: INference-time Sequence Introspection for Generating Help Triggers in Vision-Language-Action Models

arXiv:2510.01389v2 Announce Type: replace-cross Abstract: Recent Vision-Language-Action (VLA) models show strong generalization capabilities, yet they lack introspective mechanisms for anticipating fa

Inverting the Shield: Systematically Generating Safety Tests from Policy Specifications

arXiv:2605.24883v1 Announce Type: new Abstract: The widespread integration of Large Language Models (LLMs) necessitates rigorous and systematic safety evaluation. Existing paradigms either rely on con

Is Human Annotation Necessary? Iterative MBR Distillation for Error Span Detection in Machine Translation

arXiv:2603.12983v3 Announce Type: replace-cross Abstract: Error Span Detection (ESD) is a crucial subtask in Machine Translation (MT) evaluation, aiming to identify the location and severity of transl

IterInject: Indirect Prompt Injection Against LLM Agents via Feedback-Guided Iterative Optimization

arXiv:2605.24659v1 Announce Type: new Abstract: LLM-based agents are increasingly deployed for complex tasks requiring planning, tool use, and interaction with external services. Their reliance on unt

IVR-R1: Refining Trajectories through Iterative Visual-Grounded Reasoning in Reinforcement Learning

arXiv:2605.23997v1 Announce Type: cross Abstract: Multimodal large language models via reinforcement learning (RL) have demonstrated remarkable capabilities in complex visual reasoning tasks, yet they

JacQuant: STE-Free Quantization-Aware Training via Learned Jacobian Surrogates

arXiv:2605.25469v1 Announce Type: new Abstract: Quantization-aware training (QAT) is widely deployed but typically relies on the Straight-Through Estimator (STE), which passes gradients through non-di

JAEGER: Joint 3D Audio-Visual Grounding and Reasoning in Simulated Physical Environments

arXiv:2602.18527v2 Announce Type: replace-cross Abstract: Current audio-visual large language models (AV-LLMs) are predominantly restricted to 2D perception, relying on RGB video and monaural audio. T

Joint Optimization of Training and Inference in Federated Edge Learning via Constrained Multi-Objective Deep Reinforcement Learning

arXiv:2605.25916v1 Announce Type: new Abstract: Federated edge learning (FEEL) has recently emerged as a promising paradigm for achieving edge intelligence (EI) via enabling collaborative model traini

safetyarxiv-cs-lg

JT-SAFE-V2: Safety-by-Design Foundation Model with World-Context Data

arXiv:2605.24414v1 Announce Type: new Abstract: We introduce JT-Safe-V2, a large language model designed to advance the safety and trustworthiness of foundation models, extending our previous JT-Safe

KAME: Tandem Architecture for Enhancing Knowledge in Real-Time Speech-to-Speech Conversational AI

arXiv:2510.02327v2 Announce Type: replace-cross Abstract: Real-time speech-to-speech (S2S) models excel at generating natural, low-latency conversational responses but often lack deep knowledge and se

Know You Before You Speak: User-State Modeling for LLM Personalization in Multi-Turn Conversation

arXiv:2605.24647v1 Announce Type: new Abstract: Personalized dialogue requires more than recalling explicit user histories: systems also need to infer hidden user states that evolve through interactio

applicationsarxiv-cs-cl

Knowledge Graph Re-engineering Along the Ontological Continuum (extended version)

arXiv:2605.22093v2 Announce Type: replace Abstract: Knowledge graphs have become the primary vehicle for data integration and are critical to the success of modern AI, but the diversity of KG modellin

applicationsarxiv-cs-ai

KT4EQG: Personalized Exercise Question Generation via Knowledge Tracing

arXiv:2605.23933v1 Announce Type: cross Abstract: Educational Question Generation (EQG) aims to synthesize customized exercise questions that enhance student learning. An effective EQG system should i

L2IR: Revealing Latent Intent in Graph Fraud Detection

arXiv:2605.26040v1 Announce Type: new Abstract: Graph fraud detection has long depended on Graph Neural Networks (GNNs) to propagate and aggregate information across relational data. A critical obstac

applicationsarxiv-cs-ai

Language Movement Primitives: Grounding Language Models in Robot Motion

arXiv:2602.02839v3 Announce Type: replace Abstract: Enabling robots to perform novel manipulation tasks from natural language instructions remains a fundamental challenge in robotics, despite signific

applicationsarxiv-cs-ro

Large Language Model Selection with Limited Annotations

arXiv:2605.24981v1 Announce Type: new Abstract: Choosing a Large Language Model (LLM) for a given task requires comparing many strong candidates, yet standard evaluation relies on costly annotations o

researcharxiv-cs-cl

LC-ERD: Mining Latent Logic for Self-Evolving Reasoning via Consistency-Regulated Reward Decomposition

arXiv:2605.24005v1 Announce Type: new Abstract: The evolution of Large Language Model (LLM) reasoning is bottlenecked by the scarcity of high-quality process data. While self-alignment via endogenous

Learning Concepts, Not Tokens: Self-Supervised Semantic Alignment for Language Models

arXiv:2603.29123v2 Announce Type: replace Abstract: The next-token prediction (NTP) objective trains language models to predict a single token at each step, even though many continuations can express

safetyarxiv-cs-cl

Learning Fine-grained Parameter Sharing via Sparse Tensor Decomposition

arXiv:2411.09816v4 Announce Type: replace Abstract: Large neural networks achieve state-of-the-art performance on many tasks, yet their sheer size hinders deployment on resource-constrained devices. A

Learning Laplacian Eigenspace with Mass-Aware Neural Operators on Point Clouds

arXiv:2605.24390v1 Announce Type: new Abstract: The eigendecomposition of the Laplace--Beltrami Operator (LBO) is fundamental to geometric analysis, yet computing its low-frequency eigenmodes remains