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Semantics at an Angle: When Cosine Similarity Works Until It Doesn't

arXiv:2504.16318v3 Announce Type: replace Abstract: Cosine similarity is a standard comparison rule for learned representations in information retrieval, natural language processing, computer vision,

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Research

ShriNep@EEUCA 2026: RAKSHAK - Multi-Task DeBERTa with Rationale Distillation and Jigsaw-Augmented Training for Toxic Intent Classification

DGX agent

arXiv:2607.20450v1 Announce Type: new Abstract: This paper presents two systems for the GameTox Shared Task at the Workshop on EEUCA at ACL 2026, which requires classifying World of Tanks chat utteran

researcharxiv-cs-cl

24 Jul 2026

SiGMA: Sign-Guided Merging and Adaptation for Multimodal Continual Instruction Tuning

arXiv:2607.20511v1 Announce Type: new Abstract: Multimodal Continual Instruction Tuning (MCIT) is crucial for adapting Multimodal Large Language Models (MLLMs) to evolving a sequence of downstream tas

Sparse Concept Channels in Frozen 3D CT Vision Encoders

arXiv:2607.20993v1 Announce Type: cross Abstract: Large vision-language models are becoming increasingly dominant in 3D medical image interpretation, but we rarely know which internal units encode cli

SPDCN: Strip-based Deformable Convolutional Network for Steel Surface Defect Segmentation

arXiv:2607.21456v1 Announce Type: new Abstract: Steel surface defect segmentation is critical for industrial quality inspection, yet existing methods struggle with elongated, anisotropic defects such

Spectral Concentration and Recovery in Sparse High-Dimensional Random Geometric Graphs

arXiv:2607.14304v2 Announce Type: replace-cross Abstract: We study sparse threshold random geometric graphs generated by high-dimensional spherical or Gaussian latent vectors. Although each edge has m

Stochastic Sampling is Epistemically Shallow: The Dimensionality Gap Between Temperature Variation and Model Diversity in LLMs

arXiv:2607.20464v1 Announce Type: new Abstract: When a language model gives different answers on repeated runs, does that variation reveal what it does not know? Self-consistency turns the variation i

StrideDiffusion: Accelerating Diffusion Models for Time-series Generation

arXiv:2607.20545v1 Announce Type: new Abstract: Diffusion models have become competitive generators for time series, but their practical use is limited by the large number of sequential denoising step

Structure-Preserving Physics-Informed Neural Network for the Korteweg--de Vries (KdV) Equation

arXiv:2511.00418v2 Announce Type: replace Abstract: Physics-Informed Neural Networks (PINNs) offer a flexible framework for solving nonlinear partial differential equations (PDEs), yet conventional im

SubSplat: High-Resolution Pixel-aligned 3DGS via Sub-pixel Gaussian Reparameterization

arXiv:2607.20813v1 Announce Type: new Abstract: Pixel-aligned Gaussian splatting enables efficient and generalizable novel-view synthesis. However, high-resolution rendering faces a critical trade-off

Surprisal Theory is Tautological (without Rational Grounding)

arXiv:2607.21574v1 Announce Type: new Abstract: Surprisal theory holds that the human processing difficulty of a linguistic unit in context is an affine function of its surprisal under some language m

TabPFN beyond Tabular Data: Calibration and Accuracy on Multimodal Embeddings

arXiv:2607.11007v2 Announce Type: replace Abstract: Few-shot multimodal classification commonly attaches a lightweight head, such as k-nearest neighbors, logistic regression, or a linear SVM, to a fro

Tackling Heterogeneity in Federated Learning via Variance-Reduced Boltzmann Sampling within Homogeneous Social Coalitions

arXiv:2506.02897v3 Announce Type: replace Abstract: Federated Learning (FL) enables privacy-preserving collaborative model training, but its effectiveness is often limited by client data heterogeneity

Texture++: Elevating 3D Asset Texture Resolution with a Region-Aware Diffusion Model

arXiv:2607.21504v1 Announce Type: new Abstract: Numerous 3D assets are discarded due to low texture resolution, while current super-resolution models ignore texture maps and focus on natural images. A

The Active Ingredient in Muon's Grokking

arXiv:2607.20512v1 Announce Type: cross Abstract: The Muon optimizer reaches the grokking threshold on modular arithmetic faster than AdamW. Prior work attributes this to 'spectral-norm constraints pl

The Human-AI Substitution Principle: When will you be replaced by AI in your organization?

arXiv:2607.20781v1 Announce Type: new Abstract: Artificial Intelligence (AI) is rapidly transforming organizations, raising a fundamental organizational and economic question: when will a human employ

The Price of Hidden Curvature: An widetilde{Omega} (d^{5/4} sqrt{T}) Lower Bound for Bandit Convex Optimization

arXiv:2607.18652v2 Announce Type: replace-cross Abstract: We establish a widetildeOmega(d^{5/4}sqrt T) lower bound on the minimax expected regret of stochastic bandit convex optimization of 1-Lipschit

The Weight of Silence: A Causal Case for Weights Over the Scratchpad in Latent Chess Reasoning

arXiv:2607.20952v1 Announce Type: cross Abstract: Latent, or silent, reasoning lets language models carry out intermediate computation in continuous vector space instead of words, and is widely assume

Thermodynamic Weight Decay: Exploring Grokking Acceleration via Attention Specific Heat

arXiv:2607.20552v1 Announce Type: new Abstract: Grokking -- the delayed generalization of neural networks long after they have memorized their training data -- wastes thousands of training epochs and

Thinkink: 2D Spatial Ink-native Interaction with LLMs

arXiv:2607.21468v1 Announce Type: cross Abstract: People often use handwritten notes and sketches to externalize ideas for ideation. To integrate large language models (LLMs) into this practice, we pr

Towards a Certifying Grounder

arXiv:2607.21199v1 Announce Type: cross Abstract: Grounding, the translation of high-level theories into equivalent quantifier-free formulas, is a crucial step in declarative solving, yet it has so fa

Towards Capability-Aware Traversability Navigation for Unstructured Environments

arXiv:2607.20679v1 Announce Type: new Abstract: Estimating traversability in unstructured environments requires conditioning on robot embodiment, as the same terrain can be traversable for one platfor

researcharxiv-cs-ro

Towards Robust Iris Recognition Through Occlusion Identification and Conditional Diffusion-Based Reconstruction

arXiv:2607.21545v1 Announce Type: new Abstract: Iris recognition is a reliable biometric approach that identifies individuals using the distinctive and stable texture of the iris. However, recognition

Tractable Hierarchical Control of Autoregressive Language Models

arXiv:2607.20483v1 Announce Type: new Abstract: Constraining the generation of autoregressive large language models (LLMs) is an important component of integrating language models into formal systems.

Transformer-Assisted LLM-Based Source Code Summarisation: to Enable More Secure Software Development

arXiv:2607.20933v1 Announce Type: cross Abstract: Neural Source Code Summarisation (NSCS) aims to generate natural language summaries of source code to improve developers' and maintainers' understandi

Transformer-based Diffusion models for Hydrological Time Series Probabilistic Imputation and Forecasting

arXiv:2607.21200v1 Announce Type: cross Abstract: The modeling of hydrometeorological time series with limited observations is a key challenge in the monitoring of hydro-systems and water resources, a

Uncertainty-Aware Trust Estimation for Multi-LLM Systems via Structured Expert Judgement

arXiv:2607.20529v1 Announce Type: cross Abstract: Large Language Model (LLM) ensembles are increasingly used to improve reliability by combining predictions from multiple LLMs. However, existing aggre

Unified Video Dense Prediction from Disjoint Data

arXiv:2607.21592v1 Announce Type: new Abstract: Scene understanding requires simultaneous prediction about geometry, appearance, and semantics. However, existing task-specific annotations are fragment

Unsupervised Consensus-Based Anomaly Detection for Spatiotemporal Malaria Incidence in Ghana

arXiv:2607.21559v1 Announce Type: new Abstract: A consensus anomaly detection framework was applied to monthly malaria surveillance data from Ghana (2014-2023) to identify atypical transmission patter

Unsupervised Metal Artifact Reduction in Dental CBCT using Fine-tuned Cycle-Consistent Adversarial Networks

arXiv:2607.20977v1 Announce Type: new Abstract: Metal artifacts generated by dental implants significantly degrade cone-beam computed tomography (CBCT) volumes, obscuring critical anatomical structure

VeriSimpl: Robust Optimization Modeling from Natural Language using Simplification-based Verification

arXiv:2607.20474v1 Announce Type: new Abstract: Natural language interfaces can greatly benefit the accessibility and usability of optimization modeling, and recent advances in large language models (

WAT3R: Feedforward Underwater 3D Reconstruction

arXiv:2607.21023v1 Announce Type: new Abstract: Reliable feedforward underwater 3D reconstruction remains challenging due to severe light attenuation and backscattering, which degrade visual quality a

Where Animacy Lives in Large Language Models: Tracing the Circuits of the Animacy Concept

arXiv:2607.20995v1 Announce Type: new Abstract: Distinguishing animate from inanimate concepts in written language requires more than shallow text processing, as it involves recognizing complex select

Writhe-Based Polymer Link Classification Using Machine Learning

arXiv:2607.20657v1 Announce Type: cross Abstract: Unique and rapid classification of knots and links is an open mathematical problem that is relevant to a range of (bio)physical systems, including pol

A Bayesian Framework for Built-in Input Dimension Reduction for Gaussian Process Modeling

arXiv:2607.19498v1 Announce Type: cross Abstract: Gaussian process (GP) modeling is widely used in computational science and engineering. However, fitting a GP to high-dimensional inputs remains chall

A Confidence Interval for the ell_2 Expected Calibration Error

arXiv:2408.08998v4 Announce Type: replace-cross Abstract: Recent advances in machine learning have significantly improved prediction accuracy in various applications. However, ensuring the calibration

A Deep Learning Framework for Predicting Solar EUV Irradiance During Significant Flares

arXiv:2607.19597v1 Announce Type: cross Abstract: We present FlareEUV, a multimodal deep learning framework for predicting daily extreme ultraviolet (EUV) irradiance at 6.5 nm over three consecutive d

A Splitting Architecture for Exact Reduced Coulomb Friction

arXiv:2607.19599v1 Announce Type: cross Abstract: Existing approaches to frictional contact dynamics typically either modify the Coulomb law to improve numerical robustness or solve the exact law in a

researcharxiv-cs-ro

A Structure-Adaptive Random Feature Method for High-Dimensional Elliptic PDEs

arXiv:2607.19786v1 Announce Type: cross Abstract: Random-feature methods reduce high-dimensional elliptic PDE collocation to linear coefficient problems, but full-dimensional trial spaces overlook low

A Unified Variational Framework for Deep Weakly Supervised Image Segmentation

arXiv:2607.19669v1 Announce Type: new Abstract: We propose a unified variational framework for image segmentation under sparse pixel-level supervision. Our method is based on a simplex-constrained Pot

Adaptive Bayesian Online Learning via Expert Aggregation

arXiv:2607.20239v1 Announce Type: cross Abstract: Bayesian online learning promises uncertainty-aware prediction on data streams, but its performance hinges on inferential choices, including learning

Adaptive deep nonparametric regression from dependent data under covariate shift

arXiv:2607.20309v1 Announce Type: cross Abstract: Covariate shift often occurs because, in many real applications, the source and the target observations may be generated from different distributions.

Adaptive Multi-Expert Graph Transformer for Interpretable EEG-Based Diagnostics

arXiv:2607.19429v1 Announce Type: new Abstract: Electroencephalographic (EEG) abnormalities arise from dynamic changes in neural synchrony across spatial and temporal scales, yet many computational ap

Adaptive Visual Autoregressive Acceleration via Dual-Linkage Entropy Analysis

arXiv:2602.01345v2 Announce Type: replace Abstract: Visual AutoRegressive modeling (VAR) suffers from substantial computational cost due to the massive token count involved. Failing to account for the

AdaRoPE: Not All Attention Heads Should Rotate and Scale Equally

arXiv:2607.19363v1 Announce Type: new Abstract: Rotary Position Embedding (RoPE) is widely adopted in Transformers to encode positional information, yet standard implementations enforce a uniform freq

Adversarial Frontiers: Minimum-Norm Attack Ensembles for Robustness Evaluation

arXiv:2607.19855v1 Announce Type: new Abstract: Adversarial robustness is commonly evaluated with predefined attack ensembles, such as AutoAttack, at a single perturbation budget arepsilon and on a se

An Intelligent-Cloud Edge Multimodal Interaction System for Robots

arXiv:2607.14675v2 Announce Type: replace-cross Abstract: Robust human-robot interaction in complex environments requires accurate gesture perception, semantic scene understanding, and reliable task p

An Isotropy-Preserving Spectral Cap for Muon: Theory and Three Case Studies

arXiv:2607.19771v1 Announce Type: cross Abstract: Muon and related matrix-sign optimizers are increasingly used to pre-train large language models, but their effect on the internal geometry of individ