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Sparse Prototype Code Underlies Classification and Prediction Across Modalities

arXiv:2608.15632v1 Announce Type: cross Abstract: Neural representations have become a central tool for studying the internal mechanisms of modern AI models, yet their complex high-dimensional structu

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Spectral Gaps of Hit-and-Run and Coordinate Hit-and-Run

DGX agent

arXiv:2608.16878v1 Announce Type: cross Abstract: For any convex body KsubsetR^{n} containing a unit ball, the spectral gap of Hit-and-Run is Omega(1/(n^2 C_{mathsf{PI}})), where C_{mathsf{PI}} is the

researcharxiv-cs-lg

18 Aug 2026

Spectral Saliency for Machine Unlearning

arXiv:2608.15548v1 Announce Type: cross Abstract: Machine unlearning (MU) aims to remove the influence of specific training data while preserving model utility. As the name suggests, MU can be viewed

Spinning Conformal Correlators from Neural Networks

arXiv:2608.15001v1 Announce Type: cross Abstract: We construct spinning conformal fields from neural networks and the embedding formalism, computing their two-, three- and four-point functions in exam

SplatGuide: Geometric Priors from 3D Gaussians for Pose-Free Novel View Synthesis

arXiv:2608.16863v1 Announce Type: new Abstract: Generating photorealistic novel views from unposed images requires both 3D geometric understanding and the ability to synthesize unseen content. A natur

SQuad: Sub-Quadratic Attention Distillation for Efficient Video Generation

arXiv:2608.16585v1 Announce Type: new Abstract: Video Diffusion Transformers (DiTs) spend most of their compute inside the Self-Attention operation, whose cost grows quadratically, O(n^2), with the nu

STAIR: Semantic-Temporal Automaton for Interpretable Reasoning in Temporal Question Answering

arXiv:2608.16224v1 Announce Type: cross Abstract: By leveraging large-scale pretraining, LLMs can interpret diverse temporal expressions and question formulations without task-specific training. Howev

Static Pruning Across Sparse Retrieval Regimes: What Transfers, What Breaks, and What Still Helps

arXiv:2608.16309v1 Announce Type: cross Abstract: Static pruning is widely used to accelerate sparse neural retrieval, yet existing studies each validate their conclusions within a single custom pipel

Steering the Flow: Inverting Face Recognition Models via Gradient-Guided Flow Matching

arXiv:2608.16791v1 Announce Type: cross Abstract: Model Inversion Attacks (MIAs) aim to reconstruct representative training samples of target identities from face recognition models, exposing critical

Stop Indexing at Full Precision: Revisiting Clustering for Vector Embeddings

arXiv:2608.14648v1 Announce Type: cross Abstract: In this study, we revisit three widely used techniques in vector search and utilize them to optimize vector embedding indexing through clustering: dim

Structuring Semantic Embeddings for Principle Evaluation: A Prototype-Guided Contrastive Learning Approach

arXiv:2608.15224v1 Announce Type: new Abstract: Reliable post-hoc evaluation asks whether already generated text satisfies a target criterion after generation. In this paper we study a focused frozen-

Sufficient Dimesion Reduction via Generalized Stein's Lemma

arXiv:2608.15121v1 Announce Type: cross Abstract: Sufficient dimension reduction (SDR) seeks the minimal subspace of the predictors that captures the full conditional distribution of the response, whi

Sum-of-Squares Degree Barriers for the Reweighted-Hinge Method in Robust Halfspace Learning: A Christoffel-Function Characterization

arXiv:2606.17215v2 Announce Type: replace Abstract: A certificate that removes outliers sees the data only through its low-degree moments, and an adversary exploits exactly this, hiding corruption whe

Synthetic Data Augmentation for Satellite-Based Analysis of Battle-Damaged Agricultural Fields in Ukraine

arXiv:2608.16380v1 Announce Type: cross Abstract: Monitoring war-induced damage to agricultural land in Ukraine is important for understanding threats to food security, environmental stability, and po

T-LLM Compiler: Trusted LLM-based Code Optimization and Verification Framework

arXiv:2608.14953v1 Announce Type: new Abstract: Recent advances in Large Language Models (LLMs) have opened opportunities to apply high-level code transformations to the field of code optimization, an

Tabletop Pen Manipulation With a Vision-Guided 4-DoF Arm

arXiv:2608.15968v1 Announce Type: new Abstract: Low-cost four-degree-of-freedom (DoF) arms are among the most accessible robotic platforms. But they are, in theory, underactuated for picking up in sit

researcharxiv-cs-ro

Task-Driven Three-Layer Distributed Scheduling for Emergency Earth Observation in Large Low-Earth-Orbit Constellations

arXiv:2608.14789v1 Announce Type: new Abstract: Large low-Earth-orbit (LEO) Earth-observation (EO) constellations offer frequent access to geographically dispersed ground targets, but emergency reques

Temporal Graph Prototype-conditioned Conformal Prediction for Fraud Detection

arXiv:2608.15768v1 Announce Type: cross Abstract: Conformal prediction (CP) provides distribution-free coverage guarantees and has emerged as a principled tool for uncertainty quantification. In edge-

Test-Time Instance Selection for Improved Whole Slide Image Analysis

arXiv:2608.14759v1 Announce Type: cross Abstract: Whole Slide Image (WSI) analysis has been widely studied for cancer diagnosis. Conventionally, a gigapixel WSI is divided into small patches and proce

The canonical facets of multi-separator polytopes

arXiv:2608.16861v1 Announce Type: cross Abstract: We initiate a polyhedral study of the graph multi-separator problem proposed by Irmai et al. (2024) as an alternative to the lifted multicut problem f

The Distributional View of Knowledge Distillation

arXiv:2608.15215v1 Announce Type: cross Abstract: Token-level knowledge distillation (KD) matches two conditional distributions per position, yet the standard objectives compare them pointwise: a Kull

The Download: how people really use AI, and Flock’s design choices

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. We still don’t know how people are really using AI AI companie

researchmit-tech-review

The Limits of Binding in Dual Encoders

arXiv:2608.15971v1 Announce Type: cross Abstract: Dual-encoder models such as CLIP score an image-caption pair by a single inner product of two independently computed unit vectors, and fail at binding

researcharxiv-cs-cl

The Many Senses of Visual Similarity: A Text-Prompted Image Perceptual Metric

arXiv:2607.18237v2 Announce Type: replace Abstract: Human visual similarity judgments are context-dependent. For example, two images may be similar in shape but distinct in color. Existing perceptual

The Null Token Knows: Reducing Message-Free Hallucination in ASR and NMT

arXiv:2608.15940v1 Announce Type: new Abstract: Modern encoder-decoder systems can produce fluent text even when their input contains no recoverable message. We study this failure in ASR and NMT throu

researcharxiv-cs-cl

The Open-Strategy Dictator Game: Cooperation Under Mutual Transparency

arXiv:2608.14913v1 Announce Type: cross Abstract: We introduce the Open-Strategy Dictator Game (OSDG), a variant of the classic dictator game in which each player's strategy is a natural-language docu

The Physical Cutoff Does Not Restore Homogenization: Phase-Dependent Burning in the Strain G-Equation

arXiv:2608.15337v1 Announce Type: cross Abstract: We disprove the expectation stated by Xin, Yu, and Ronney that the physical positive part strain G-equation should possess an effective burning veloci

The Quantum Shortcut: Complex Phase-State Dynamics Reduce the Optimization Steps of Sequence Models

arXiv:2608.14691v1 Announce Type: new Abstract: Sequence models are conventionally distinguished by their backbone, the mechanism that routes information across positions, such as attention or recurre

The Right Prior for the Right Deformation: Rethinking Continuous Deformable Image Registration

arXiv:2608.16146v1 Announce Type: new Abstract: Deformable image registration models implicitly encode deformation priors through their parametrization and optimization. In this work, we conduct a val

The Value of a Prompt: An LLM-Relative Kolmogorov-Complexity Approach

arXiv:2608.16438v1 Announce Type: new Abstract: In a world where valuable artifacts are increasingly created, completed, or processed by LLMs, the central economic question is not only what the LLM ca

Thinking Outside the (Gray) Box: A Context-Based Score for Assessing Value and Originality in Neural Text Generation

arXiv:2502.13207v4 Announce Type: replace-cross Abstract: Despite the increasing use of large language models for creative tasks, their outputs often lack diversity. Common solutions, such as sampling

TIMA: Text-Image Mutual Awareness for Balancing Zero-Shot Adversarial Robustness and Generalization Ability

arXiv:2405.17678v2 Announce Type: replace-cross Abstract: Achieving zero-shot adversarial robustness without sacrificing generalization remains challenging for foundation models such as CLIP, especial

Time to Reason: Scalable Neurosymbolic Learning for LTLf via Fuzzy Semantics

arXiv:2608.16443v1 Announce Type: new Abstract: Neurosymbolic (NeSy) Artificial Intelligence aims to integrate Deep Learning (DL) architectures with symbolic reasoning. While initial NeSy approaches h

TokenSTFormer: A Tokenized Spatial-temporal Attention Model for Holistic Motion Analysis in Adolescent Idiopathic Scoliosis Screening

arXiv:2608.16122v1 Announce Type: cross Abstract: Adolescent Idiopathic Scoliosis (AIS) is a prevalent spinal deformity in adolescents that, if left untreated, can result in severe health outcomes. Tr

Toward Optimal Second-Order Path-Length Guarantee for Adversarial Multi-Armed Bandits

arXiv:2608.15996v1 Announce Type: new Abstract: We study second-order path-length regret in adversarial K-armed bandits against oblivious loss sequences. Bubeck et al. [2019] designed an algorithm tha

Towards Computational Provenance: Carrying Causal-State Evidence in Generated Text

arXiv:2608.16868v1 Announce Type: cross Abstract: A language model's output does not by itself provide verifiable evidence about the internal computation that produced it. We study computational prove

Training-Free Long-Term Multi-Object Tracking for Sports Video Analytics

arXiv:2608.15688v1 Announce Type: new Abstract: Long-term multi-object tracking in sports remains challenging due to frequent occlusions, rapid camera motion, and repeated player reappearances. We int

Training-Free Multi-Concept Image Editing

arXiv:2602.20839v3 Announce Type: replace Abstract: Training-free image editing with diffusion models is highly desirable yet is complex and remains a significant challenge. While recent optimisation-

Transfer Learning of Keystroke Dynamics for Cross-Device User Authentication

arXiv:2608.16334v1 Announce Type: new Abstract: Keystroke dynamics (typing patterns) can be used as a behavioural biometric modality for user authentication, with applications such as fraud prevention

TransfHAR: Self-Supervised Wrist Representations for On-Demand Activity Recognition

arXiv:2608.15861v1 Announce Type: new Abstract: Fine-grained wrist activity recognition can support applications such as procedural step guidance and context-aware assistance, yet acquiring labeled da

Translating finite-domain integer constraint models to CP/SMT/ILP/PB/SAT solvers with CPMpy

arXiv:2608.15143v1 Announce Type: new Abstract: Constraint solving is a declarative approach for solving combinatorial satisfaction and optimization problems. The user specifies their problem through

Turning spectra into images improves plant trait retrieval with 2D-CNNs

arXiv:2608.16661v1 Announce Type: new Abstract: Hyperspectral reflectance spectroscopy enables non-destructive estimation of plant functional traits, yet current deep learning approaches process spect

Two by Two: Learning Multi-Task Pairwise Objects Assembly for Generalizable Robot Manipulation

arXiv:2504.06961v2 Announce Type: replace-cross Abstract: 3D assembly tasks, such as furniture assembly and component fitting, play a crucial role in daily life and represent essential capabilities fo

UC-VLM: Consistency-Driven Learning for AI-Generated Image Detection with Vision-Language Large Models

arXiv:2608.15238v1 Announce Type: new Abstract: Vision-Language Large Models (VLLMs) are promising for AI-generated image (AIGI) detection because they can produce both a prediction and a natural-lang

Ultra: Unsupervised Cross-Task Optimization for Reliable Restoration Segmentation Collaboration under Adverse Weather

arXiv:2608.16589v1 Announce Type: new Abstract: Unsupervised Domain Adaptation for Adverse Weather Semantic Segmentation (UDA-ASS) aims to transfer semantic knowledge from labeled normal-weather image

Uncertainty Identifies Difficult Samples Across Methods: A Multi-Task Study on a Heterogeneous Skin Lesion Dataset

arXiv:2608.14768v1 Announce Type: new Abstract: Skin lesion classifiers can be confidently wrong on the cases that matter most, so knowing when a prediction should not be trusted is clinically as usef

Uncovering Hidden Leptonic Correlations with Flow Matching and Autoencoders

arXiv:2608.15042v1 Announce Type: cross Abstract: We perform a global search for values of the Yukawa matrices and Majorana masses in the Type-I seesaw mechanism. Using flow matching, which is a gener

Understanding AI Anxiety in the Workplace: A Multimethod Investigation Using Fear Acquisition Theory and the Technology Acceptance Model

arXiv:2608.14609v1 Announce Type: cross Abstract: As artificial intelligence (AI) rapidly diffuses and concerns about job displacement intensify, the psychological mechanisms underlying AI job replace