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How Prolific Sellers Self-Present: Dissecting the Communication Patterns of 1.6 Million Reverb Listings

arXiv:2608.29952v1 Announce Type: new Abstract: The current paper draws on self-presentation theory and warranting theory to evaluate how the language patterns in an online marketplace reflect seller

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How You Ask Shapes What You Get: A Theory-Seeded Measurement of Articulation in Advice-Seeking LLM Conversations

DGX agent

arXiv:2608.29591v1 Announce Type: new Abstract: Users articulate the same advice-seeking request in different ways: some specify detailed constraints, others gesture at a vague need. Prior work treats

researcharxiv-cs-cl

1 Sept 2026

Hybrid Semantic Context-Enhanced Ensemble Learning for Wind Power Ramp-Event Forecasting and Uncertainty-Aware Evaluation

arXiv:2608.29024v1 Announce Type: new Abstract: Wind power ramp events which are sudden, large swings in turbine output over short windows are difficult to estimate, and standard models often miss the

Hydra: A Navigation World Action Model with Discrete Latent Planning and Continuous Flow-Matching Execution

arXiv:2608.28995v1 Announce Type: cross Abstract: World models let robots imagine possible futures, but exploiting this capability for real-time control is bottlenecked by a representation misalignmen

Hyper-Fold: Exploring the Expressive Limit of Sequence-Geometry Learning for Proteins via Hypergraph Modeling

arXiv:2608.29207v1 Announce Type: new Abstract: Protein structure modeling rests on a single computational primitive: the interaction between what a residue is (sequence content) and where it sits (th

Identity-Conditioned Latent Consistency Distillation for Face Synthesis

arXiv:2608.31053v1 Announce Type: new Abstract: Diffusion models have achieved strong results in high-fidelity image synthesis, but their iterative sampling process makes large-scale generation comput

Implementing neural network mixed-effects models in Template Model Builder (TMB)

arXiv:2608.31133v1 Announce Type: cross Abstract: Neural network mixed-effects models (NMMs) have gained traction by combining the strong representation and predictive power of artificial neural netwo

Improving Image-to-Image Translation via a Rectified Flow Reformulation

arXiv:2603.20186v2 Announce Type: replace Abstract: In this work, we propose Image-to-Image Rectified Flow Reformulation (I2I-RFR), a practical plug-in reformulation that recasts standard I2I regressi

Improving Randomized Metric Distortion to 2.3282

arXiv:2608.29308v1 Announce Type: cross Abstract: In metric social choice, each voter ranks a set of m candidates by her distance to them in an unknown metric space. The cost of a candidate is its ave

Improving Spatial-Temporal Reasoning in Video-Language Models with Structured Video Prompting

arXiv:2608.28666v1 Announce Type: new Abstract: Video-language models (VLMs) remain brittle on tasks that require tracking events over time and grounding answers in specific spatial regions. We propos

Informative Label Missingness in Multiclass Classification Information Geometry and Excess Risk

arXiv:2608.30561v1 Announce Type: cross Abstract: Informative label missingness can change the usual efficiency ordering between completely and partially labelled classifiers because the pattern of mi

InfScene-SR: Seamless Super-Resolution of Arbitrarily Large Remote-Sensing Scenes via Variance-Preserving Joint Denoising

arXiv:2602.19736v3 Announce Type: replace Abstract: Diffusion models now give the best perceptual quality in super-resolution (SR), but their architecture and training confine them to small fixed crop

Integrating Triaxial IMU Sensors and Ensemble Learning for Effective Parkinson Disease Severity Classification

arXiv:2608.28602v1 Announce Type: new Abstract: Parkinson disease PD is a progressive neurodegenerative disease that can have a significant impact on motor performance resulting in the appearance of s

Intelligent Identification and Repair of Design Defects in BIM via Domain-Specific Large Language Models

arXiv:2608.28629v1 Announce Type: cross Abstract: Existing methods lack a generalized approach to efficiently identify and resolve the diversity of design defects in BIM. Therefore, this study propose

Jigsaw-CRL: Recovering Global Latent Causal Order from Fragmented Multi-Client Interventions

arXiv:2608.28991v1 Announce Type: cross Abstract: Causal representation learning (CRL) aims to recover latent causal variables and their structural relations from high-dimensional observations. Existi

Keyframe-Centric State-Space Modeling for Burst Image Super-Resolution

arXiv:2503.19634v2 Announce Type: replace Abstract: Burst image super-resolution (BISR) reconstructs a high-resolution keyframe by aggregating complementary sub-pixel evidence from a short burst of lo

Knowing Beyond the Known: Reinforced Knowledge Specification for Multi-Label Class-Incremental Learning

arXiv:2608.30316v1 Announce Type: new Abstract: Existing class-incremental learning methods struggle in multi-label scenarios (MLCIL) due to the inherent contradiction of learning objectives arising f

Kolmogorov--Arnold against bounded translations

arXiv:2608.30710v1 Announce Type: new Abstract: Historically originating from Hilbert's 13th problem, the Kolmogorov-Arnold representation theorem (KART) has recently experienced a major revitalisatio

Kronecker Factorization Improves Efficiency and Interpretability of Sparse Autoencoders

arXiv:2505.22255v4 Announce Type: replace-cross Abstract: Sparse Autoencoders (SAEs) decompose language-model activations into sparse, interpretable features, but standard encoders usually treat the l

Language Proficiency Assessment from Eye Movements in Naturalistic Passage Reading

arXiv:2608.30583v1 Announce Type: new Abstract: Standard language proficiency tests rely on linguistic tasks such as vocabulary, grammar and reading comprehension quizzes. An alternative, cognitively

LARC: Lazy Adaptive Reachability Certification of Robot Manipulator Trajectories

arXiv:2608.29767v1 Announce Type: new Abstract: Discrete trajectory checks can miss collisions between sampled robot states. Reachability-based certification bounds motion between states, but uniform

researcharxiv-cs-ro

Large Language Models and Evolutionary Computation: A Critical Review of Bidirectional Interaction, Automated Algorithm Design, and Co-Adaptive Systems

arXiv:2505.15741v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) and Evolutionary Computation (EC) are increasingly being combined to support automated optimization, algorithm de

LCoT-GV: Graph Attention Networks for Verifying Long Reasoning Chains in Large Language Models

arXiv:2608.30679v1 Announce Type: cross Abstract: Large Reasoning Models produce Long Chains-of-Thought (LCoTs) which involve breaking down the problem into smaller reasoning steps before reaching the

Learning Composable Chains-of-Thought

arXiv:2505.22635v2 Announce Type: replace-cross Abstract: A common approach for teaching large language models (LLMs) to reason is to train on chain-of-thought (CoT) traces of in-distribution reasonin

Learning from Many Voices: Literary MT Using Multi-Reference Human and Synthetic Data

arXiv:2412.18707v3 Announce Type: replace Abstract: Multiple valid translations of a single literary work naturally exist. We investigate strategies for leveraging these multi-reference datasets to im

Learning Human Health and Diseases from 24-hour Wrist Movement

arXiv:2608.29494v1 Announce Type: new Abstract: Much of human health and function unfolds beyond the clinic, through the movements of everyday life. Wrist-worn accelerometers capture these movements c

Learning Representations through Token Prediction: Geometry, Approximation, and Downstream Guarantees

arXiv:2608.30072v1 Announce Type: cross Abstract: Token prediction is a central pre-training objective for modern language models. Despite its empirical success, why token prediction learns broadly us

Learning-Theoretic Foundation for General Coded Computing: The Straggler Setting

arXiv:2608.28910v1 Announce Type: new Abstract: Coded computing has emerged as a powerful paradigm for mitigating the impact of straggling workers in distributed computing systems. However, existing c

Learning to Restore More: Continual Capability Expansion for Pretrained Image Restoration Models

arXiv:2608.30305v1 Announce Type: new Abstract: Image restoration models are typically trained with a fixed set of capabilities. When new restoration requirements emerge, existing solutions usually tr

Learning Where Outcomes Change:Credit-Addressable Reasoning for Multimodal Geometry

arXiv:2608.30457v1 Announce Type: cross Abstract: Multimodal geometry reasoning requires VLMs to extract precise visual relations and preserve them through multi-step deduction. Existing free-form tra

Least but not Last: Fine-tuning Intermediate Principal Components for Better Performance-Forgetting Trade-Offs

arXiv:2602.03493v2 Announce Type: replace Abstract: Low-Rank Adaptation (LoRA) methods have emerged as crucial techniques for adapting large pre-trained models to downstream tasks under computational

Leveraging Turn-taking Dynamics for Intent Recognition in Multi-party Conversations

arXiv:2608.28926v1 Announce Type: new Abstract: We propose a multi-task learning approach for multi-party dialogue intent recognition that leverages an auxiliary task that models turn-taking dynamics.

LightFuse: Relightable Interactive Gaussian Scene Reconstruction via Multi-Scan Fusion and 2D Gaussian Ray Tracing

arXiv:2608.29269v1 Announce Type: new Abstract: Relightable interactive scene reconstruction aims to build an editable 3D model from scans of different object arrangements and render new layouts under

Linguistic Distance Segregates Latent Representations in Automatic Speech Recognition Systems

arXiv:2608.30853v1 Announce Type: new Abstract: While automatic speech recognition (ASR) models have achieved remarkable improvements in recent years, performance disparities persist across different

LLM-Based Knowledge Graph Completion Combining Discrete Structural Coding with Similar Entity Information

arXiv:2608.30235v1 Announce Type: new Abstract: Knowledge graph completion requires models to use both textual descriptions and relational structure. Existing LLM-based methods either encode KG struct

Look It Up: Analysing Internal Web Search Capabilities of Modern LLMs

arXiv:2511.18931v2 Announce Type: replace-cross Abstract: Modern large language models increasingly integrate internal web-based retrieval to provide real-time answers, yet it remains unclear how effe

Mapping-Based Image Diffusion

arXiv:2608.29164v1 Announce Type: new Abstract: In this work, we introduce a novel tensor-based functional for targeted image enhancement and denoising. Via explicit regularization, our formulation in

Matrix-Game 3.5: Enhancing Real-Time Streaming Interactive World Models with Patch Memory

arXiv:2608.29910v1 Announce Type: new Abstract: Interactive world models extend video generation from offline clip synthesis toward persistent simulation of interactive virtual worlds, enabling applic

MCSeg: Pre-training and Fine-tuning Volumetric Pyramid Transformer for Multi-modal Cardiac Image Segmentation

arXiv:2608.30371v1 Announce Type: new Abstract: Automatic cardiac image segmentation is pivotal for diagnosing and treating cardiac diseases. In this work, we introduce MCSeg, a volumetric transformer

Measuring Memory and Generalization as Separable Geometric Channels: The Topo^2 Framework

arXiv:2608.30487v1 Announce Type: cross Abstract: Deep networks trained on noisy labels simultaneously generalize on clean data and memorize flipped labels. These are usually conflated as pressures on

Measuring Similarity between Artistic and AI Generated Images using Siamese Neural Networks

arXiv:2608.28671v1 Announce Type: cross Abstract: AI-generated art has sparked debates around potential plagiarism, as these images may closely resemble existing artworks. This research quantifies the

Medical Foundation Model Features as Perceptual Loss for Brain MRI Contrast Dose Simulation

arXiv:2608.28773v1 Announce Type: cross Abstract: Perceptual losses are widely used in medical image synthesis because they encourage agreement in high-level structure beyond voxel-wise intensity simi

MedTVL: Harnessing Vision and Language for Medical Time Series Classification

arXiv:2608.28605v1 Announce Type: new Abstract: Recent advancements in multimodal learning for medical time series (MedTS) classification highlight the benefits of integrating complementary modalities

MEL: Coordinate-Preserving EEG Tokenization for fMRI Translation

arXiv:2608.29304v1 Announce Type: new Abstract: Translating electroencephalography (EEG) into functional magnetic resonance imaging (fMRI) is important for medical neuroimaging, clinical brain-state m

Membership is Ownership: A Robust Ownership Verification Framework for Diffusion Models

arXiv:2608.28929v1 Announce Type: cross Abstract: Large-scale diffusion models have fueled numerous profitable downstream applications for AI-related businesses, including visual editing and content c

MEMORA: Embodied Action Memory from Egocentric Videos for Reasoning and Planning

arXiv:2607.14252v2 Announce Type: replace-cross Abstract: Embodied agents accumulate experience over time. We study how accumulated experience can be formed into persistent memory for future reasoning

MiBOT: A head-worn robot that modulates cardiovascular responses through human-like soft massage

arXiv:2608.30055v1 Announce Type: new Abstract: Massage therapy is helpful for the rehabilitation of various diseases, such as headaches caused by migraines and stress. Existing robotic systems have f

researcharxiv-cs-ro

Minerals in the Wild: A Hyperspectral-XRF Dataset for Elemental Composition Estimation

arXiv:2608.30537v1 Announce Type: new Abstract: Rapid mineral characterization is essential for applications ranging from mineral exploration to industrial ore processing. To this end, Hyperspectral I