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A Progress-Aware Leader-Follower Midair Docking System for Dual-Drone Aerial Manipulation

model-releasesarxiv-cs-ro

arXiv:2605.29410v1 Announce Type: new Abstract: Reliable midair docking between small unmanned aerial vehicles (UAVs) is essential for modular aerial cooperation and manipulation, but it requires prec

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Research

A Quotient Homology Theory of Representation in Neural Networks

DGX agent

arXiv:2502.01360v4 Announce Type: replace Abstract: Previous research has proven that the set of maps implemented by neural networks with a ReLU activation function is identical to the set of piecewis

researcharxiv-cs-lg

29 May 2026

A Review of Learning-Based Motion Planning: Toward a Data-Driven Optimal Control Approach

arXiv:2512.11944v2 Announce Type: replace-cross Abstract: Motion planning for autonomous driving (AD) faces a critical trade-off. While traditional rule-based pipelines offer verifiable safety and int

A Study on Question-Answer Dataset for LLM Safety Evaluation with a Focus on Illegal Activities

arXiv:2605.29340v1 Announce Type: new Abstract: In this paper, we discuss question-answer dataset for LLM safety evaluation, with a focus on illegal activities. Specifically, on the basis of manual an

safetyarxiv-cs-cl

A Survey on Recent Advances in Conversational Data Generation

arXiv:2405.13003v2 Announce Type: replace-cross Abstract: Recent advancements in conversational systems have significantly enhanced human-machine interactions across various domains. However, training

A Systematic Evaluation of Molecular Mixture Behavior Prediction

arXiv:2605.29698v1 Announce Type: new Abstract: Machine learning for molecular property prediction has focused largely on pure compounds, even though many practical applications depend on mixtures wit

Applications

A Theoretical and Experimental Study of a Novel Adaptive Learning Algorithm

arXiv:2605.29273v1 Announce Type: new Abstract: A crucial component of machine learning algorithms is minimizing loss functions with less computational cost and less oscillations. While adaptive learn

applicationsarxiv-cs-lg

A Training-Time Diagnostic for Generalization via the Log-Alignment Ratio

arXiv:2605.28975v1 Announce Type: new Abstract: We study the log-alignment ratio (LAR), a measure of parameter-activation alignment, introduced in parameterization theory. We reformulate it as the ove

A Triple-Modal Contrastive Learning Framework with Sequence, Graph, and 3D Features for Drug-Target Interaction Prediction

arXiv:2605.29926v1 Announce Type: new Abstract: Accurate prediction of drug-target interactions (DTI) is critical for drug discovery. Existing methods often rely on single-modal representations (e.g.,

A unified deeplearning framework for contrast-phase-specific virtual monochromatic imaging

arXiv:2605.29753v1 Announce Type: cross Abstract: Dual-energy CT (DECT) enables virtual monochromatic imaging (VMI) and improved contrast resolution, but its clinical adoption is limited by hardware c

Accelerating Constrained Decoding with Token Space Compression

arXiv:2605.29986v1 Announce Type: new Abstract: To guarantee that an LLM's outputs conform to a specified structure, context-free grammar (CFG) decoding engines force the selection of next tokens that

Local Ai

Accelerating HEVC Intra Partitioning via a CNN-Hierarchical Attention Transformer Hybrid

arXiv:2605.29063v1 Announce Type: cross Abstract: The recursive quad-tree partitioning in High Efficiency Video Coding (HEVC) incurs considerable computational overhead, with exhaustive rate-distortio

local-aiarxiv-cs-cv

Access Sets Matter: Budgeting Expert Reads for Scalable Weight-Space Model Merging

arXiv:2605.29489v1 Announce Type: new Abstract: Weight-space model merging is usually formulated as an algebraic operation on checkpoints, yet at LLM scale the limiting resource is often the set of ex

Applications

Accommodation Goes Both Ways: Studying Linguistic Convergence Between Humans and Language Models

arXiv:2605.29278v1 Announce Type: new Abstract: As LLMs become increasingly integrated into daily life, understanding how their presence will shape human linguistic behavior is an open question. We pr

applicationsarxiv-cs-cl

Achieving Linear Speedup for Composite Federated Learning

arXiv:2602.03357v2 Announce Type: replace Abstract: This paper proposes FedNMap, a normal map-based method for composite federated learning, where the objective consists of a smooth loss and a possibl

Active Continual Learning with Metaplastic Binary Bayesian Neural Networks

arXiv:2605.30198v1 Announce Type: new Abstract: Always-on edge systems must keep learning as conditions change under tight compute budgets and must detect unreliable predictions. Bayesian binary neura

Active Learning for Machine Learning Driven Molecular Dynamics

arXiv:2509.17208v3 Announce Type: replace Abstract: Machine-learned coarse-grained (CG) potentials are fast, but degrade over time when simulations reach under-sampled bio-molecular conformations, and

ActTraitBench: Quantifying the Knowledge-Decision Gap in Large Language Models via Human-Grounded Behavioral Validation

arXiv:2605.29791v1 Announce Type: new Abstract: While Large Language Models (LLMs) can convincingly simulate personas in explicit self-reports, they often deviate in implicit behavioral decisions, rev

safetyarxiv-cs-cl

Adapting Automotive Aerodynamics Surrogates to New Vehicle Families via Transfer Learning

arXiv:2605.27968v1 Announce Type: cross Abstract: Deploying Scientific Machine Learning surrogates in industrial CFD workflows requires adapting pretrained models to new vehicle families without large

Adapting Multilingual Embedding Models to Turkish via Cross-Lingual Tokenizer Surgery and Offline Distillation

model-releasesarxiv-cs-cl

arXiv:2605.29992v1 Announce Type: new Abstract: Sentence embeddings are a foundational component for semantic search, clustering, classification, and retrieval-augmented generation. This paper present

Adaptive Exponential Integration for Stable Gaussian Mixture Black-Box Variational Inference

arXiv:2601.14855v3 Announce Type: replace Abstract: Black-box variational inference (BBVI) with Gaussian mixture families offers a flexible approach for approximating complex posterior distributions w

Adaptive Interviewing for Persona Simulation in LLMs: Evidence-Grounded Reasoning Improves Decision Alignment

arXiv:2605.29458v1 Announce Type: cross Abstract: Accurately simulating the decisions of a specific individual remains challenging for large language models (LLMs), partly because persona information

Adaptive Targeted Dynamic Chunking for Tokenization-Free Hierarchical Model

arXiv:2605.30080v1 Announce Type: new Abstract: Tokenization-free hierarchical models are emerging as a promising alternative to traditional Large Language Models (LLMs), addressing inherent preproces

researcharxiv-cs-cl

AdaState: Self-Evolving Anchors for Streaming Video Generation

arXiv:2605.30349v1 Announce Type: new Abstract: Autoregressive video diffusion models generate streaming video by producing frames sequentially, conditioning each chunk on previously generated content

researcharxiv-cs-cv

Adopt neq Adapt: Longitudinal Analyses of LLM Conversations in the Wild

arXiv:2605.29018v1 Announce Type: new Abstract: Although a growing body of research has begun to describe user--LLM interactions, the picture it paints is largely static; little is known about how ind

AfriScience-MT: Towards Decolonizing Science in Africa through Text Translation

model-releasesarxiv-cs-cl

arXiv:2605.29741v1 Announce Type: new Abstract: The dominance of colonial languages in African education and scientific communication limits how hundreds of millions of speakers of African languages a

AG-REPA: Causal Layer Selection for Representation Alignment in Audio Flow Matching

arXiv:2603.01006v2 Announce Type: replace-cross Abstract: REPresentation Alignment (REPA) improves the training of generative flow models by aligning intermediate hidden states with pretrained teacher

Agent4Edu: Generating Learner Response Data by Generative Agents for Intelligent Education Systems

arXiv:2501.10332v2 Announce Type: replace-cross Abstract: Personalized learning represents a promising educational strategy within intelligent educational systems, aiming to enhance learners' practice

agentsarxiv-cs-ai

AgentCVR: Active Multi-Agent Cross-Video Reasoning via Script-Simulated Reinforcement Learning

model-releasesarxiv-cs-cv

arXiv:2605.29643v1 Announce Type: new Abstract: Cross-Video Reasoning (CVR) has emerged as a critical frontier in multimodal intelligence, requiring models to retrieve, align, and aggregate evidence d

AgentDoG 1.5: A Lightweight and Scalable Alignment Framework for AI Agent Safety and Security

arXiv:2605.29801v1 Announce Type: new Abstract: Modern open-world agents such as OpenClaw exhibit powerful cross-environment execution capabilities yet introduce broad new safety risk sources. Meanwhi

AgentDropoutV2: Optimizing Information Flow in Multi-Agent Systems via Test-Time Rectify-or-Reject Pruning

arXiv:2602.23258v2 Announce Type: replace Abstract: While Multi-Agent Systems (MAS) excel in complex reasoning, they suffer from the cascading impact of erroneous information from individual agents. C

AgentSchool: An LLM-Powered Multi-Agent Simulation for Education

arXiv:2605.30144v1 Announce Type: new Abstract: Despite the rapid deployment of LLMs into classrooms, validating educational AI remains uniquely intractable: interventions act on developing learners w

agentsarxiv-cs-ai

Aggregate Models, Not Explanations: Improving Feature Importance Estimation

arXiv:2602.11760v2 Announce Type: replace-cross Abstract: Feature-importance methods show promise in transforming machine learning models from predictive engines into tools for scientific discovery. H

Agora: Toward Autonomous Bug Detection in Production-Level Consensus Protocols with LLM Agents

arXiv:2605.29910v1 Announce Type: cross Abstract: Consensus protocols form the backbone of distributed systems and blockchains, where implementation bugs can cause data corruption and financial losses

AIRGuard: Guarding Agent Actions with Runtime Authority Control

arXiv:2605.28914v1 Announce Type: cross Abstract: Tool-using language agents turn model decisions into external side effects: they read files, run scripts, call APIs, send messages, and invoke Model C

Aligned but Fragile: Enhancing LLM Safety Robustness via Zeroth-Order Optimization

arXiv:2605.29396v1 Announce Type: new Abstract: Safety alignment for large language models (LLMs) aims to reduce harmful or unsafe behavior while preserving general utility. However, recent findings r

Alignment-Guided Score Matching for Text-to-Image Alignment in Diffusion Models

arXiv:2605.30038v1 Announce Type: cross Abstract: Diffusion models generate highly realistic images but often struggle with precise text-image alignment. While recent post-training methods improve ali

AlignVid: Training-Free Attention Scaling for Semantic Fidelity in Text-Guided Image-to-Video Generation

model-releasesarxiv-cs-cv

arXiv:2512.01334v2 Announce Type: replace Abstract: Text-guided image-to-video generation has made substantial progress, yet it still struggles to execute text-specified edits that require substantial

AliMark: Enhancing Robustness of Sentence-Level Watermarking Against Text Paraphrasing

arXiv:2605.29434v1 Announce Type: cross Abstract: Existing sentence-level watermarking methods enhance robustness to paraphrasing by anchoring watermarks in sentence semantics. However, their prefix-b

Ambient-robust Inverse Rendering using Active RGB-NIR Imaging

arXiv:2605.30250v1 Announce Type: new Abstract: Inverse rendering aims to reconstruct geometry and reflectance of objects from images. Despite recent progress, existing methods often produces inaccura

researcharxiv-cs-cv

AMDP: Asynchronous Multi-Directional Pipeline Parallelism for Large-Scale Models Training

arXiv:2605.29664v1 Announce Type: cross Abstract: Pipeline parallelism is essential for large-scale model training, but existing asynchronous approaches often degrade convergence due to parameter mism

An accuracy-aware extension to LRP-based pruning for CNNs to prevent cascading accuracy degradation in data-scarce transfer learning

arXiv:2511.10861v3 Announce Type: replace-cross Abstract: Convolutional Neural Networks (CNNs) pre-trained on large-scale datasets such as ImageNet are widely used as feature extractors to construct h

An Approach for Thyroid Nodule Analysis Using Thermographic Images

arXiv:2605.29221v1 Announce Type: new Abstract: Thyroid cancer is said to be the second most common type of cancer in female individuals and the third in males by 2030, according to projections. In ge

agentsarxiv-cs-cv

An End-to-End PyTorch Interface for Differentiable PDE Solvers: A RANS Model-Correction Study

arXiv:2605.28858v1 Announce Type: cross Abstract: This work presents an end-to-end strategy for solving inverse problems constrained by Partial Differential Equations within a fully differentiable Mac

Analyzing Persona Effects in Generated Explanations from Multimodal LLM Agents in Urban Perception

arXiv:2605.29064v1 Announce Type: new Abstract: We study how persona prompting shapes language generated by multimodal large language models in an urban perception setting. Using 59,808 annotations fr

researcharxiv-cs-cl

Anchorless Diversification for Parallel LLM Ideation

arXiv:2605.30150v1 Announce Type: new Abstract: LLMs are increasingly used to generate candidate-idea pools for creative tasks where broad exploration is valuable. Parallel inference can be attractive

AnomalyAgent: Training-Free Agentic Models for Zero-/Few-Shot Anomaly Detection

arXiv:2605.30140v1 Announce Type: new Abstract: Benefiting from generalizability of vision-language models (VLMs) such as CLIP, many zero-/few-shot anomaly detection (AD) approaches have achieved impr

agentsarxiv-cs-cv

Anti Mode-Collapse in Mean-Field Transformer via Auxiliary Variables

arXiv:2605.30229v1 Announce Type: new Abstract: We use a mean-field-based transformer model to theoretically investigate how auxiliary variables, such as positional encoding, prevent mode collapse of