Search: “framework”

Discovering Lexical Gaps Using Embeddings from Multilingual LLMs

arXiv:2605.24310v1 Announce Type: new Abstract: Lexical gaps are words that do not exist in certain languages. They pose challenges for building multilingual lexical resources, for machine translation

safetyarxiv-cs-cl

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Distilling Game Code World Model Generation into Lightweight Large Language Models

DGX agent

arXiv:2605.24375v1 Announce Type: new Abstract: Large Language Models (LLMs) have shown great ability in generating executable code from natural language, opening the possibility of automatically cons

model-releasesarxiv-cs-ai

26 May 2026

Distinguishing Right from Wrong in Debates: Attribution Analysis of Chinese Harmful Memes

arXiv:2605.24344v1 Announce Type: new Abstract: Research on harmful meme detection has garnered significant attention, resulting in the development of numerous datasets and methods. However, progress

researcharxiv-cs-cl

Distributionally Robust Transfer Learning with Structurally Missing Covariates, with Application to Cross-National Cardiac Arrest Prediction

arXiv:2605.24212v1 Announce Type: cross Abstract: Deploying clinical prediction models across healthcare systems often fails when key training covariates are unavailable at deployment and labeled outc

Diverse via bounded Agreement: Geometric Regularization for Multimodal Fusion

arXiv:2601.21670v3 Announce Type: replace-cross Abstract: Multimodal fusion is often treated as an optimization-balancing problem, where training signals are adjusted to prevent one modality from domi

safetyarxiv-cs-lg

Don't Retrain, Just Reuse: Recovering Dual-Target Molecules from Single-Target Diffusion Models

arXiv:2605.25681v1 Announce Type: cross Abstract: Designing a single molecule that modulates two targets is a promising strategy for polypharmacology, but it remains substantially harder than standard

Applications

Double Self-weighted Multi-view Clustering via Adaptive View Fusion

arXiv:2011.10396v3 Announce Type: replace-cross Abstract: Multi-view clustering has been applied in many real-world applications where original data often contain noises. Some graph-based multi-view c

applicationsarxiv-cs-ai

DriftingMol: Decoder-Coupled Drift for One-Pass Property-Conditional Molecular Generation

arXiv:2605.24841v1 Announce Type: new Abstract: Property-conditional molecular generation should produce valid, diverse molecules while responding to continuous target values at low sampling cost. We

researcharxiv-cs-lg

DRInQ: Evaluating Conversational Implicature with Controlled Context Variation

model-releasesarxiv-cs-cl

arXiv:2605.24267v1 Announce Type: new Abstract: Human conversation relies heavily on conversational implicature, in which speakers convey meanings that are suggested rather than explicitly stated. Alt

DRIVE: Modeling Skills at the Reasoning and Interaction Levels for Web Agents under Continual Learning

arXiv:2605.23939v1 Announce Type: new Abstract: Web agents require both high-level reasoning (for task decomposition) and low-level interactions (for page elements manipulation) to conduct different t

DRScaffold: Boosting Dense-Scene Reasoning in Lightweight Vision Language Models

arXiv:2605.26038v1 Announce Type: cross Abstract: Lightweight vision-language models perform competitively on standard benchmarks yet fail systematically in dense-scene reasoning, where multiple objec

DUEL: Adversarial Self-Play for Multimodal Reasoning

arXiv:2605.24794v1 Announce Type: cross Abstract: Reinforcement learning (RL) has emerged as an effective paradigm for improving the reasoning capability of vision-language models (VLMs). However, RL-

researcharxiv-cs-cl

Dynamic Neural Koopman Distillation for Real-Time Robot Control Using Diffusion Models

arXiv:2605.24924v1 Announce Type: new Abstract: Diffusion models excel at generating diverse and multimodal trajectories for robotic planning, yet their iterative denoising process introduces latency

safetyarxiv-cs-ro

Dynamic Optimization and Safety Indicator Injection for Jailbreaking Text-to-Image Models with Multimodal Safety Filters

arXiv:2505.18979v2 Announce Type: replace Abstract: Text-to-image (T2I) models can generate not-safe-for-work (NSFW) content, motivating multi-stage safety pipelines with both text and image filters.

safetyarxiv-cs-lg

E3AD: An Emotion-Aware Vision-Language-Action Model for Human-Centric End-to-End Autonomous Driving

arXiv:2512.04733v2 Announce Type: replace-cross Abstract: End-to-end autonomous driving (AD) systems increasingly adopt vision-language-action (VLA) models, yet they typically ignore the passenger's e

EchoDistill:Alignment Noisy-to-Clean Self-Distillation for Robust Audio LLMs

arXiv:2605.23954v1 Announce Type: cross Abstract: Audio Large Language Models (ALLMs) are highly vulnerable to real-world noise, which often induces severe semantic drift and hallucinations. Existing

EchoPilot: Training-Free Ultrasound Video Segmentation via Scale-Space Semantic Prompting and Reliability-Gated Memory

arXiv:2605.25944v1 Announce Type: cross Abstract: Ultrasound video segmentation is clinically valuable yet difficult due to speckle noise, weak boundaries, and rapid anatomical deformation. Recent pro

ECo-MoE: Embodiment-Conditioned Mixture of Experts Increases the Evolvability of Robots

arXiv:2605.24225v1 Announce Type: new Abstract: In this paper, we introduce a model of evolution and learning in robots that co-optimizes a distribution of latent design vectors (genotypes) and a mixt

safetyarxiv-cs-ro

Efficient DP-SGD for LLMs with Randomized Clipping

model-releasesarxiv-cs-lg

arXiv:2605.24879v1 Announce Type: new Abstract: Large language models (LLMs) are trained on vast datasets that may contain sensitive information. Differential privacy (DP), the de facto standard for f

Efficient Long-Horizon Vision-Language-Action Models via Static-Dynamic Disentanglement

model-releasesarxiv-cs-ro

arXiv:2602.03983v3 Announce Type: replace Abstract: Vision-Language-Action (VLA) models have recently emerged as a promising paradigm for generalist robotic control. Built upon vision-language model (

Agents

EfficientGraph-RAG: Structured Retrieval-State Management for Cross-Task Retrieval-Augmented Generation

arXiv:2605.25379v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) has become the standard way to ground large language models in external knowledge, but many systems still organize

agentsarxiv-cs-cl

Emission-Aware Reinforcement Learning for Sustainable Electric Vehicle Charging and Carbon Dioxide Reduction Under Varying Renewable Penetration

arXiv:2605.24543v1 Announce Type: new Abstract: The rapid growth of Electric Vehicle (EV) adoption challenges power distribution networks through peak load spikes, voltage instability, and transformer

Emotional intelligence in large language models is fragmented across perception, cognition, and interaction

arXiv:2605.24686v1 Announce Type: new Abstract: As large language models (LLMs) are increasingly integrated into emotionally sensitive domains, the structural integrity of their emotional intelligence

End-to-End Intracortical Speech Decoding from Neural Activity

arXiv:2605.24313v1 Announce Type: new Abstract: Current high-performing intracortical speech neuroprostheses achieve low word error rates but typically rely on external language models during inferenc

researcharxiv-cs-cl

Enhancing Reliability in LLM-Based Secure Code Generation

arXiv:2605.24300v1 Announce Type: cross Abstract: Large language models (LLMs) are widely used for code generation, but their security reliability remains inconsistent across languages and prompting s

Equation-Free Coarse Control of Distributed Parameter Systems via Local Neural Operators

model-releasesarxiv-cs-lg

arXiv:2509.23975v2 Announce Type: replace-cross Abstract: The control of high-dimensional distributed parameter systems (DPS) remains a challenge when explicit coarse-grained equations are unavailable

Applications

Equip Pre-ranking with Target Attention by Residual Quantization

arXiv:2509.16931v3 Announce Type: replace-cross Abstract: The pre-ranking stage in industrial recommendation systems faces a fundamental conflict between efficiency and effectiveness. While powerful m

applicationsarxiv-cs-ai

Eureka: Intelligent Feature Engineering for Enterprise AI Cloud Resource Demand Prediction

arXiv:2605.25297v1 Announce Type: cross Abstract: Effective features are crucial for predictive model performance, but creating them often requires domain expertise, limiting scalability across applic

Evaluating passing decision-making in professional football: An enhanced MPNN approach to Receiver Selection

arXiv:2605.25696v1 Announce Type: new Abstract: The process of decision-making in football is characterized by a complex interplay between spatial positioning, opponent pressure, and player intent. Th

researcharxiv-cs-lg

Everything at Every Scale: Scale-Invariant Diffusion with Continuous Super-Resolution

arXiv:2605.26032v1 Announce Type: cross Abstract: Creating images from noise is image generation; reconstructing fine details from coarse inputs is super-resolution. Despite their practical difference

Evidence-Linked Radiology Reporting: A Human-Supervised Reference Architecture for Structured Imaging Intelligence

arXiv:2605.25120v1 Announce Type: cross Abstract: Radiology reports remain the primary mechanism by which imaging findings are communicated to clinical teams. However, much of the structured informati

Evolutionary Enhanced Multi-Agent Reinforcement Learning for Cooperative Air Combat

arXiv:2605.25091v1 Announce Type: new Abstract: As modern air combat evolves toward beyond-visual-range (BVR) multi-aircraft cooperative engagements, autonomous decision-making for unmanned combat aer

Agents

Evolutionary Physics-Informed Temporal Fusion for Lane-Change Intention Prediction

arXiv:2512.24075v5 Announce Type: replace Abstract: Early lane-change intention prediction is essential for autonomous driving and ADAS, but it remains challenging because lane-changing behavior depen

agentsarxiv-cs-lg

Local Ai

Evolving Causal Regulatory Networks (ECR-Net)

arXiv:2605.25211v1 Announce Type: new Abstract: Modern machine learning models excel at pattern recognition but remain brittle, often failing to generalize out of distribution (OOD) because they captu

local-aiarxiv-cs-lg

Explainable Retinal Imaging for Prediction of Multi-Organ Dysfunction in Type 2 Diabetes

arXiv:2605.24912v1 Announce Type: cross Abstract: Background: Type 2 diabetes mellitus (T2DM) is increasingly recognised as a systemic disease characterised by coordinated dysfunction across metabolic

Extreme Region Policy Distillation

arXiv:2605.25582v1 Announce Type: cross Abstract: Reinforcement learning for large language models faces a fundamental trade-off between sample efficiency and asymptotic performance: strictly on-polic

Extreme-value forest fire prediction A study of the Loss Function in an Ordinality Scheme

arXiv:2601.03327v3 Announce Type: replace-cross Abstract: Wildfires are highly imbalanced natural hazards in both space and severity, making the prediction of extreme events particularly challenging.

Factored Latent Action World Models

arXiv:2602.16229v2 Announce Type: replace Abstract: Learning latent actions from action-free video has emerged as a powerful paradigm for scaling up controllable world model learning. Latent actions p

safetyarxiv-cs-lg

Tutorials

Factorize to Generalize: Retrieval-Guided Invariant-Dynamic Decomposition for Time Series Forecasting

arXiv:2605.24911v1 Announce Type: cross Abstract: Time series foundation models (TSFMs) have recently achieved strong zero-shot forecasting performance through large-scale pretraining and retrieval-au

tutorialsarxiv-cs-ai

Faithfulness as Information Flow: Evaluating and Training Faithful Chain-of-Thought Reasoning

arXiv:2605.24286v1 Announce Type: cross Abstract: Chain-of-thought (CoT) reasoning is useful for monitoring language models only when the reasoning trace faithfully reflects the computation that produ

safetyarxiv-cs-cl

Few-Shot Neural Differentiable Simulator: Real-to-Sim Rigid-Contact Modeling

arXiv:2603.06218v2 Announce Type: replace Abstract: Accurate physics simulation is essential for robotic learning and control, yet analytical simulators often fail to capture complex contact dynamics,

safetyarxiv-cs-ro

FLoRIST: Singular Value Thresholding for Efficient and Accurate Federated Fine-Tuning of Large Language Models

arXiv:2506.09199v2 Announce Type: replace-cross Abstract: Integrating Low-Rank Adaptation (LoRA) into federated learning offers a promising solution for parameter-efficient fine-tuning of Large Langua

Forgettable Federated Linear Learning with Certified Data Unlearning

arXiv:2306.02216v3 Announce Type: replace Abstract: Federated Learning (FL) enables collaborative model training across distributed clients while preserving user privacy. Recently, Federated Unlearnin

researcharxiv-cs-lg

Found in Conversation: LLMs Teach Themselves to Close the Multi-Turn Gap

model-releasesarxiv-cs-cl

arXiv:2605.24432v1 Announce Type: new Abstract: Large Language Model (LLM) interactions are typically underspecified, with users clarifying all necessary details across multiple conversational turns.

Fourier Feature Pyramids for Physics-Informed Neural Networks

model-releasesarxiv-cs-lg

arXiv:2605.24278v1 Announce Type: new Abstract: We present an improved neural field architecture for solving partial differential equations (PDEs). Current physics-informed neural networks (PINNs) pro

Agents

From Accuracy to Auditability: A Survey of Determinism in Financial AI Systems

arXiv:2605.23955v1 Announce Type: new Abstract: Deploying machine learning in regulated financial environments -- credit risk, fraud detection, and anti-money laundering -- exposes critical vulnerabil

agentsarxiv-cs-ai

From Multi-Agent Systems and the Semantic Web to Agentic AI: A Unified Narrative of the Web of Agents

arXiv:2507.10644v4 Announce Type: replace Abstract: The Web of Agents (WoA) transforms the document-centric Web into an environment of autonomous agents acting on users' behalf, a vision newly tractab

Fusion Embedding for Pose-Guided Person Image Synthesis with Diffusion Model

arXiv:2412.07333v2 Announce Type: replace-cross Abstract: Pose-Guided Person Image Synthesis (PGPIS) aims to generate human images in specified poses while preserving the identity and appearance of a