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Stochastic gradient descent with initial regularization

arXiv:2608.22953v1 Announce Type: new Abstract: We analyze a variant of stochastic gradient descent with initial regularization (SGDIR) and derive dimension-free upper bounds on its expected excess ri

Stochastic Separability of Embedding Manifolds

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DGX agent

arXiv:2608.22874v1 Announce Type: cross Abstract: Neurobiological studies and representation learning have observed that representations of objects belonging to the same category in high-dimensional n

researcharxiv-cs-cv

25 Aug 2026

STONIC: A Layered Measurement Contract for LLM Value Profiling

arXiv:2608.23411v1 Announce Type: new Abstract: LLM value studies often merge questionnaire ratings, pairwise choices, and values inferred from generated text into one profile. That merge assumes that

StrategyBench: Evaluating Explicit Strategy Induction in Large Language Models

arXiv:2608.23475v1 Announce Type: new Abstract: As large language models are increasingly used in data-scarce and evolving task scenarios, few-shot in-context learning (ICL) has become a key paradigm

Stress Testing Unlearning Algorithms

arXiv:2608.22527v1 Announce Type: new Abstract: Recently, machine unlearning, the removal of specific training data influence from a model, has gained increasing attention. In large language models (L

Structured Learning on Mapper Representations

arXiv:2608.22044v1 Announce Type: cross Abstract: Modern machine learning (ML) methods are highly effective for prediction tasks, but many commonly used representations reduce complex data to fixed di

Subzero matrix completion for sparse data analysis: large-scale learning of latent low-rank structure

arXiv:2608.21607v1 Announce Type: new Abstract: We investigate when a sparse nonnegative matrix can be recovered from a real-valued matrix of much lower rank by zeroing out its negative elements. The

hardwarearxiv-cs-lg

SuperMap: A Spatio-Temporal SLAM System for Visual-Language Navigation

arXiv:2608.22896v1 Announce Type: new Abstract: Robotic navigation in human environments requires a spatio-temporal semantic representation that can rec- oncile open-vocabulary perception with long-te

researcharxiv-cs-ro

SVD-Based Typicality Maps for Out-of-Distribution Detection in Vision Transformers

arXiv:2608.23499v1 Announce Type: new Abstract: We present a method for analyzing the internal representations of Vision Transformers (ViTs) exploiting the geometry of their learned parameters. Each a

safetyarxiv-cs-cv

SWE Refactor Bench: Can Coding Agents Complete a Long-Horizon, Whole-Repository Stack Migration?

arXiv:2608.23564v1 Announce Type: cross Abstract: Modern software systems accumulate technical debt over decades of development, which makes migration expensive and largely manual. As coding agents be

SweepLSD: A One-Pass, O(width)-Memory Line Segment Detector with an Integer-Only Streaming Core and a Real-Time FPGA Realization

arXiv:2608.22086v1 Announce Type: cross Abstract: We present SweepLSD, a line segment detector that reads the image exactly once and emits each segment within a few rows of its last pixel passing the

hardwarearxiv-cs-cv

Switched Turn-based Adaptive Source Seeking Strategy using Estimation and Information-driven Direction of Improvement

arXiv:2608.23068v1 Announce Type: new Abstract: Source seeking arises in applications such as gas leak localization, radiation monitoring, and environmental surveillance, where the origin of an unknow

researcharxiv-cs-ro

Sycophants in the Courtroom: Are LLMs Fragile to Juridical Authority and Evolving Legal Standards?

arXiv:2608.21409v1 Announce Type: cross Abstract: In medicine, claims remain valid when supported by empirical evidence grounded in stable biological reality. In law, by contrast, truth is contingent,

Symbolic Neural ODEs: Learning interpretable models from time-series data

arXiv:2608.22112v1 Announce Type: new Abstract: We present a machine learning framework for identifying sparse, interpretable models of dynamical systems directly from time-series data. Our approach p

SymmAdapt: Symmetrical Flow Matching for Source-Free Domain Adaptation in Medical Image Segmentation

arXiv:2608.22532v1 Announce Type: new Abstract: Domain shift across imaging modalities and acquisition sites remains a significant barrier to the clinical deployment of segmentation models. Source-fre

researcharxiv-cs-cv

SynEHR: Joint Modeling Inter-visit Temporal Evolution and Intra-visit Clinical Structure for Longitudinal EHR Synthesis

arXiv:2608.21673v1 Announce Type: cross Abstract: Longitudinal electronic health records (EHRs) document patients' sequences of clinical visits over time, preserving the temporal evolution of disease

Syntax-Guided Diffusion Language Models with User-Integrated Personalization

arXiv:2510.01028v2 Announce Type: replace Abstract: Large language models have made revolutionary progress in generating human-like text, yet their outputs often tend to be generic, exhibiting insuffi

safetyarxiv-cs-cl

Tabular foundation models for non-tabular tasks

arXiv:2608.22594v1 Announce Type: new Abstract: Tabular foundation models (TFMs) have recently emerged as a promising paradigm for machine learning on tabular data, offering the ability to generalize

TailSieve: Partial-Rollout-Guided Tail Routing for LLM Rollouts

arXiv:2608.22788v1 Announce Type: new Abstract: Large-scale rollouts have become a core component of modern LLM systems, spanning reinforcement learning (RL) post-training, on-policy distillation (OPD

safetyarxiv-cs-ai

TANGO: Token-Aggregated Nonlinear Gating Operators for Natural and Formal Language Modeling

arXiv:2608.22117v1 Announce Type: cross Abstract: A standard Transformer block separates cross-token interaction in self-attention from a nonlinear feed-forward network applied independently at each p

Targeted Iterative Filtering

arXiv:2608.22299v1 Announce Type: new Abstract: The assessment of image denoising results depends on the respective application area, i.e. image compression, still-image acquisition, and medical image

researcharxiv-cs-cv

Task-Driven 3D Printability Assistance via Geometry- and Knowledge-Grounded LLM Reasoning

arXiv:2608.22128v1 Announce Type: new Abstract: Printability assessment in additive manufacturing is typically conducted at the geometry level before printing to determine whether a computer-aided des

TASSO: TAsk-Specific Subspace Optimization for Continual Learning of Vision-Language Models

arXiv:2608.21487v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) exhibit strong zero-shot capabilities, making them an attractive solution for continual learning across diverse tasks. H

Tutorials

Teaching LLMs How ICU Physicians Approach Clinical Reasoning Through OMOP-Aligned Retrieval Improves Reasoning Across Clinical Domains

arXiv:2608.22622v1 Announce Type: cross Abstract: Clinical decision-making relies on identifying relevant patient information to guide diagnosis and treatment, a challenge that is especially difficult

tutorialsarxiv-cs-ai

TEE-X: TEE-aware Acceleration Framework for Large Vision Models at the Edge

arXiv:2608.22716v1 Announce Type: cross Abstract: Despite their remarkable success, machine learning models, particularly in vision applications, are alarmingly vulnerable to a range of security threa

safetyarxiv-cs-ai

TELEVAL: A Benchmark Designed for Spoken Language Models in Chinese Interactive Scenarios

arXiv:2507.18061v4 Announce Type: replace-cross Abstract: Spoken Language Models (SLMs) are expected to support natural spoken interaction beyond task completion. However, existing SLM benchmarks prim

Tensor Seeks Layout: Formalizing Layout Selection for ML Compilers

arXiv:2608.21555v1 Announce Type: cross Abstract: Modern machine learning compilers select tensor memory layouts to minimize execution cost under hardware constraints. Layout selection is global: an o

hardwarearxiv-cs-lg

Agents

TessIndex: Capability Verified Identity System for the Agent Economy

arXiv:2608.21942v1 Announce Type: new Abstract: Software systems have traditionally been organized around applications where human users act as principal decision-makers. Recent developments in agenti

agentsarxiv-cs-ai

Test-Time Adaptation for ECG Classification via SQI-Gated Self-Training and Beat-Rhythm Consistency

arXiv:2608.23347v1 Announce Type: new Abstract: Deep learning models for electrocardiogram (ECG) classification often suffer from significant performance degradation when deployed in unseen domains du

Text-ADBench: Text Anomaly Detection Benchmark Based on LLM Embeddings

arXiv:2507.12295v2 Announce Type: replace-cross Abstract: Text anomaly detection is a critical task in natural language processing (NLP), with applications spanning fraud detection, misinformation ide

Text-Anchored Semantic Perturbations for Transferable Jailbreak Attacks on Multimodal Large Language Models

arXiv:2608.22312v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have achieved remarkable progress in vision-language interaction, yet their safety alignment remains vulnerable

safetyarxiv-cs-cl

Text-Guided Visual Dependency Graph Learning with Cross-Modal Attention Priors

model-releasesarxiv-cs-cv

arXiv:2608.21443v1 Announce Type: new Abstract: Estimating interpretable conditional-dependence structures from multimodal visual-linguistic features remains largely unexplored. We propose CM-GLasso (

The Abstention Protocol: RCA for Clos Fabrics

arXiv:2608.21412v1 Announce Type: new Abstract: Root cause analysis (RCA) in large datacenter networks is challenging because telemetry is noisy, partial, and asynchronous. Score-based approaches degr

applicationsarxiv-cs-ai

The Axiomatic Trader: Latent Regularity, Information Budgets, and the Canonical Form of a Quantitative Investment System

arXiv:2608.23416v1 Announce Type: new Abstract: Systematic trading rests on one article of faith: that regularities found in the past persist. We state it as a time-invariant mechanism driven by an un

The Chase Is the Curriculum, the Capture Anchors the Credit: Pursuit-Evasion Self-Play for Zero-Data LLM Reasoning

arXiv:2608.21871v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards has become the dominant recipe for improving large language model reasoning, yet it presumes large human-

Agents

The Collaboration Tax: How Much LLM Multi-Agent Systems Pay to Coordinate

arXiv:2608.22152v1 Announce Type: new Abstract: Multi-agent systems built from large language models are deployed widely, yet how much performance is lost when two LLMs must coordinate rather than act

agentsarxiv-cs-cl

The Communication Map of a Transformer

arXiv:2608.22007v1 Announce Type: cross Abstract: The components of a transformer communicate by writing to and reading from a shared residual stream, and mechanistic interpretability has mapped these

hardwarearxiv-cs-cl

The Compaction Cliff in Long-Running AI Agent Memory

arXiv:2608.22752v1 Announce Type: new Abstract: A safety rule and an episodic log compete for the same tokens in an AI agent's context. When the budget overflows, both are summarized at the same rate;

The Emergence of Relevance Through Axiomatic Attention Patterns During LoRA Fine-Tuning

arXiv:2608.23338v1 Announce Type: cross Abstract: LoRA fine-tuning is standard for adapting LLMs to reranking, but it remains unclear where in the network task-specific relevance behavior is learned a

researcharxiv-cs-ai

The Error of Deep Operator Networks Is the Sum of Its Parts: Branch-Trunk and Mode Error Decompositions

arXiv:2602.21910v2 Announce Type: replace Abstract: Operator learning has the potential to strongly impact scientific computing by learning solution operators for differential equations, potentially a

The geometry of AI validation: Exact certification limits for iid best-of-N search

arXiv:2608.21496v1 Announce Type: new Abstract: AI systems increasingly generate alternatives, inspect evidence, and deploy a selected output. Validation is therefore target-relative: evidence certifi

applicationsarxiv-cs-lg

The Geometry of Low-Resource Language Representations

arXiv:2608.23358v1 Announce Type: new Abstract: The performance gap between low- and high-resource languages in LLMs is widely known, but it remains unclear which internal model factors drive these di

The Illusion of Control: Why Bare Classifier Inversion Silently Fails in Concept-Bottleneck Text Generation

arXiv:2608.22956v1 Announce Type: new Abstract: Concept-bottleneck controllable generation routes multi-attribute control through a low-dimensional concept code that, at deployment, must be synthesise

applicationsarxiv-cs-cl

The Imitator Game: Benchmarking Robot Imitative Ability Beyond Action Prediction

arXiv:2608.22301v1 Announce Type: cross Abstract: Humans imitate at the level of intent: given a demonstration, we infer its goal and carry it out with whatever tools, objects, and layouts are at hand

Agents

The Interaction Tax: When Communication Erases Diversity in Multi-Agent Teams

arXiv:2608.23541v1 Announce Type: cross Abstract: Does multi-agent LLM interaction help or hurt? Some work reports gains from debate (Du et al., 2024), critique loops (Chen et al., 2025), and mixture-

agentsarxiv-cs-ai

The Laws of Context Allocation: Causal Measurement and Closed-Loop Orchestration in Generative Search

arXiv:2608.23252v1 Announce Type: cross Abstract: As Retrieval-Augmented Generation (RAG) shifts toward diverse portfolio generation, it is stymied by two critical bottlenecks: flawed measurement of e

applicationsarxiv-cs-cl

The Mask Is Not the Model: Auditing Prefix Invariance in Attention, State-Space, and Hybrid Sequence Models

arXiv:2608.22876v1 Announce Type: cross Abstract: We formalize prefix invariance: representations at position t must not depend on future inputs. We give a lightweight audit, two forward passes, no tr

The Measurement Revolution? Credible Measurement and Inference in the Age of AI

arXiv:2608.23524v1 Announce Type: cross Abstract: Artificial intelligence (AI) is transforming measurement in economics. AI models convert unstructured data, such as text and images, into structured v

researcharxiv-cs-ai