Search: “framework”

Incentivizing Honesty among Competitors in Collaborative Learning and Optimization

model-releasesarxiv-cs-lg

arXiv:2305.16272v5 Announce Type: replace Abstract: Collaborative learning techniques have the potential to enable training machine learning models that are superior to models trained on a single enti

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Inductive Reasoning for Temporal Knowledge Graphs with Emerging Entities

DGX agent

arXiv:2604.10164v1 Announce Type: new Abstract: Reasoning on Temporal Knowledge Graphs (TKGs) is essential for predicting future events and time-aware facts. While existing methods are effective at ca

researcharxiv-cs-ai

14 Apr 2026

Influencing Humans to Conform to Preference Models for RLHF

arXiv:2501.06416v3 Announce Type: replace-cross Abstract: Designing a reinforcement learning from human feedback (RLHF) algorithm to approximate a human's unobservable reward function requires assumin

INSPATIO-WORLD: A Real-Time 4D World Simulator via Spatiotemporal Autoregressive Modeling

arXiv:2604.07209v2 Announce Type: replace Abstract: Building world models with spatial consistency and real-time interactivity remains a fundamental challenge in computer vision. Current video generat

Inspectable AI for Science: A Research Object Approach to Generative AI Governance

arXiv:2604.11261v1 Announce Type: new Abstract: This paper introduces AI as a Research Object (AI-RO), a paradigm for governing the use of generative AI in scientific research. Instead of debating whe

researcharxiv-cs-ai

Agents

Instructing LLMs to Negotiate using Reinforcement Learning with Verifiable Rewards

arXiv:2604.09855v1 Announce Type: new Abstract: The recent advancement of Large Language Models (LLMs) has established their potential as autonomous interactive agents. However, they often struggle in

agentsarxiv-cs-ai

Applications

Intelligent Approval of Access Control Flow in Office Automation Systems via Relational Modeling

arXiv:2604.11040v1 Announce Type: new Abstract: Office automation (OA) systems play a crucial role in enterprise operations and management, with access control flow approval (ACFA) being a key compone

applicationsarxiv-cs-ai

Local Ai

Intelligent bear deterrence system based on computer vision: Reducing human bear conflicts in remote areas

arXiv:2503.23178v2 Announce Type: replace Abstract: Conflicts between humans and bears on the Tibetan Plateau present substantial threats to local communities and hinder wildlife preservation initiati

local-aiarxiv-cs-cv

Intent-aligned Formal Specification Synthesis via Traceable Refinement

arXiv:2604.10392v1 Announce Type: cross Abstract: Large language models are increasingly used to generate code from natural language, but ensuring correctness remains challenging. Formal verification

Interactive Learning for LLM Reasoning

arXiv:2509.26306v4 Announce Type: replace Abstract: Existing multi-agent learning approaches have developed interactive training environments to explicitly promote collaboration among multiple Large L

Interpretable Alzheimer's Diagnosis via Multimodal Fusion of Regional Brain Experts

arXiv:2512.10966v2 Announce Type: replace-cross Abstract: Accurate and early diagnosis of Alzheimer's disease (AD) is critical for effective intervention and requires integrating complementary informa

Intersectional Sycophancy: How Perceived User Demographics Shape False Validation in Large Language Models

arXiv:2604.11609v1 Announce Type: new Abstract: Large language models exhibit sycophantic tendencies--validating incorrect user beliefs to appear agreeable. We investigate whether this behavior varies

Intra-finger Variability of Diffusion-based Latent Fingerprint Generation

arXiv:2604.10040v1 Announce Type: new Abstract: The primary goal of this work is to systematically evaluate the intra-finger variability of synthetic fingerprints (particularly latent prints) generate

Iterative Inference-time Scaling with Adaptive Frequency Steering for Image Super-Resolution

arXiv:2512.23532v2 Announce Type: replace Abstract: Diffusion models have become a leading paradigm for image super-resolution (SR), but existing methods struggle to guarantee both the high-frequency

K-STEMIT: Knowledge-Informed Spatio-Temporal Efficient Multi-Branch Graph Neural Network for Subsurface Stratigraphy Thickness Estimation from Radar Data

arXiv:2604.09922v1 Announce Type: cross Abstract: Subsurface stratigraphy contains important spatio-temporal information about accumulation, deformation, and layer formation in polar ice sheets. In pa

KCS: Diversify Multi-hop Question Generation with Knowledge Composition Sampling

arXiv:2508.20567v2 Announce Type: replace Abstract: Multi-hop question answering faces substantial challenges due to data sparsity, which increases the likelihood of language models learning spurious

researcharxiv-cs-cl

KiseKloset for Fashion Retrieval and Recommendation

arXiv:2506.23471v2 Announce Type: replace-cross Abstract: The global fashion e-commerce industry has become integral to people's daily lives, leveraging technological advancements to offer personalize

Knowing What to Stress: A Discourse-Conditioned Text-to-Speech Benchmark

model-releasesarxiv-cs-cl

arXiv:2604.10580v1 Announce Type: new Abstract: Spoken meaning often depends not only on what is said, but also on which word is emphasized. The same sentence can convey correction, contrast, or clari

Knowledge Integration in Differentiable Models: A Comparative Study of Data-Driven, Soft-Constrained, and Hard-Constrained Paradigms for Identification and Control of the Single Machine Infinite Bus System

model-releasesarxiv-cs-lg

arXiv:2602.09667v2 Announce Type: replace Abstract: Integrating domain knowledge into neural networks is a central challenge in scientific machine learning. Three paradigms have emerged -- data-driven

KSDiff: Keyframe-Augmented Speech-Aware Dual-Path Diffusion for Facial Animation

arXiv:2509.20128v2 Announce Type: replace-cross Abstract: Audio-driven facial animation has made significant progress in multimedia applications, with diffusion models showing strong potential for tal

researcharxiv-cs-ai

Large Language Models Can Help Mitigate Barren Plateaus in Quantum Neural Networks

arXiv:2502.13166v3 Announce Type: replace-cross Abstract: In the era of noisy intermediate-scale quantum (NISQ) computing, Quantum Neural Networks (QNNs) have emerged as a promising approach for vario

LARY: A Latent Action Representation Yielding Benchmark for Generalizable Vision-to-Action Alignment

arXiv:2604.11689v1 Announce Type: new Abstract: While the shortage of explicit action data limits Vision-Language-Action (VLA) models, human action videos offer a scalable yet unlabeled data source. A

LASQ: A Low-resource Aspect-based Sentiment Quadruple Extraction Dataset

arXiv:2604.10417v1 Announce Type: new Abstract: In recent years, aspect-based sentiment analysis (ABSA) has made rapid progress and shown strong practical value. However, existing research and benchma

researcharxiv-cs-cl

LAST: Leveraging Tools as Hints to Enhance Spatial Reasoning for Multimodal Large Language Models

arXiv:2604.09712v1 Announce Type: cross Abstract: Spatial reasoning is a cornerstone capability for intelligent systems to perceive and interact with the physical world. However, multimodal large lang

Latent attention on masked patches for flow reconstruction

arXiv:2603.02028v2 Announce Type: replace Abstract: Vision transformers have shown outstanding performance in image generation, yet their adoption in fluid dynamics remains limited. We introduce the L

researcharxiv-cs-lg

LEADER: Learning Reliable Local-to-Global Correspondences for LiDAR Relocalization

arXiv:2604.11355v1 Announce Type: new Abstract: LiDAR relocalization has attracted increasing attention as it can deliver accurate 6-DoF pose estimation in complex 3D environments. Recent learning-bas

Applications

Learnable Motion-Focused Tokenization for Effective and Efficient Video Unsupervised Domain Adaptation

arXiv:2604.09955v1 Announce Type: new Abstract: Video Unsupervised Domain Adaptation (VUDA) poses a significant challenge in action recognition, requiring the adaptation of a model from a labeled sour

applicationsarxiv-cs-cv

Learning 3D Representations for Spatial Intelligence from Unposed Multi-View Images

arXiv:2604.10573v1 Announce Type: new Abstract: Robust 3D representation learning forms the perceptual foundation of spatial intelligence, enabling downstream tasks in scene understanding and embodied

Learning Aligned Stability in Neural ODEs Reconciling Accuracy with Robustness

arXiv:2509.21879v2 Announce Type: replace Abstract: Despite Neural Ordinary Differential Equations (Neural ODEs) exhibiting intrinsic robustness, existing methods often impose Lyapunov stability for f

safetyarxiv-cs-lg

Learning and Enforcing Context-Sensitive Control for LLMs

arXiv:2604.10667v1 Announce Type: cross Abstract: Controlling the output of Large Language Models (LLMs) through context-sensitive constraints has emerged as a promising approach to overcome the limit

Learning from Contrasts: Synthesizing Reasoning Paths from Diverse Search Trajectories

arXiv:2604.11365v1 Announce Type: new Abstract: Monte Carlo Tree Search (MCTS) has been widely used for automated reasoning data exploration, but current supervision extraction methods remain ineffici

Learning from Emptiness: De-biasing Listwise Rerankers with Content-Agnostic Probability Calibration

arXiv:2604.10150v1 Announce Type: new Abstract: Generative listwise reranking leverages global context for superior retrieval but is plagued by intrinsic position bias, where models exhibit structural

Local Ai

Learning Hierarchical and Geometry-Aware Graph Representations for Text-to-CAD

arXiv:2604.10075v1 Announce Type: new Abstract: Text-to-CAD code generation is a long-horizon task that translates textual instructions into long sequences of interdependent operations. Existing metho

local-aiarxiv-cs-ai

Learning How Much to Think: Difficulty-Aware Dynamic MoEs for Graph Node Classification

arXiv:2604.11473v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) architectures offer a scalable path for Graph Neural Networks (GNNs) in node classification tasks but typically rely on static

researcharxiv-cs-lg

Learning Racket-Ball Bounce Dynamics Across Diverse Rubbers for Robotic Table Tennis

model-releasesarxiv-cs-ro

arXiv:2604.11349v1 Announce Type: new Abstract: Accurate dynamic models for racket-ball bounces are essential for reliable control in robotic table tennis. Existing models typically assume simple line

Learning Robustness at Test-Time from a Non-Robust Teacher

arXiv:2604.11590v1 Announce Type: new Abstract: Nowadays, pretrained models are increasingly used as general-purpose backbones and adapted at test-time to downstream environments where target data are

Learning to Forget -- Hierarchical Episodic Memory for Lifelong Robot Deployment

arXiv:2604.11306v1 Announce Type: cross Abstract: Robots must verbalize their past experiences when users ask 'Where did you put my keys?' or 'Why did the task fail?' Yet maintaining life-long episodi

Learning to Test: Physics-Informed Representation for Dynamical Instability Detection

arXiv:2604.10967v1 Announce Type: new Abstract: Many safety-critical scientific and engineering systems evolve according to differential-algebraic equations (DAEs), where dynamical behavior is constra

safetyarxiv-cs-lg

Learning World Models for Interactive Video Generation

arXiv:2505.21996v3 Announce Type: replace-cross Abstract: Foundational world models must be both interactive and preserve spatiotemporal coherence for effective future planning with action choices. Ho

LIDARLearn: A Unified Deep Learning Library for 3D Point Cloud Classification, Segmentation, and Self-Supervised Representation Learning

arXiv:2604.10780v1 Announce Type: new Abstract: Three-dimensional (3D) point cloud analysis has become central to applications ranging from autonomous driving and robotics to forestry and ecological m

LLM-based Realistic Safety-Critical Driving Video Generation

arXiv:2507.01264v2 Announce Type: replace-cross Abstract: Designing diverse and safety-critical driving scenarios is essential for evaluating autonomous driving systems. In this paper, we propose a no

LMMs Meet Object-Centric Vision: Understanding, Segmentation, Editing and Generation

arXiv:2604.11789v1 Announce Type: new Abstract: Large Multimodal Models (LMMs) have achieved remarkable progress in general-purpose vision--language understanding, yet they remain limited in tasks req

Locket: Robust Feature-Locking Technique for Language Models

arXiv:2510.12117v3 Announce Type: replace-cross Abstract: Chatbot service providers (e.g., OpenAI) rely on tiered subscription plans to generate revenue, offering black-box access to basic models for

researcharxiv-cs-lg

LOOPE: Learnable Optimal Patch Order in Positional Embeddings for Vision Transformers

arXiv:2504.14386v2 Announce Type: replace-cross Abstract: Positional embeddings (PE) play a crucial role in Vision Transformers (ViTs) by providing spatial information otherwise lost due to the permut

researcharxiv-cs-ai

LottieGPT: Tokenizing Vector Animation for Autoregressive Generation

arXiv:2604.11792v1 Announce Type: new Abstract: Despite rapid progress in video generation, existing models are incapable of producing vector animation, a dominant and highly expressive form of multim

Low-rank Optimization Trajectories Modeling for LLM RLVR Acceleration

arXiv:2604.11446v1 Announce Type: cross Abstract: Recently, scaling reinforcement learning with verifiable rewards (RLVR) for large language models (LLMs) has emerged as an effective training paradigm

LRD-Net: A Lightweight Real-Centered Detection Network for Cross-Domain Face Forgery Detection

arXiv:2604.10862v1 Announce Type: new Abstract: The rapid advancement of diffusion-based generative models has made face forgery detection a critical challenge in digital forensics. Current detection

Local Ai

Machine-learning modeling of magnetization dynamics in quasi-equilibrium and driven metallic spin systems

arXiv:2604.11513v1 Announce Type: cross Abstract: We review recent advances in machine-learning (ML) force-field methods for large-scale Landau-Lifshitz-Gilbert (LLG) simulations of metallic spin syst

local-aiarxiv-cs-lg