Search: “model-releases”

Pathology Transport: Optimal-Transport Explanations for Clinical Data, and When Their Heatmaps (Fail to) Localize Disease

arXiv:2608.17370v1 Announce Type: new Abstract: Generative models promise a route to explainable clinical AI: rather than probe a classifier, model the distributions of healthy and diseased patients a

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Model Releases

Picture the Epsilon: Pursuing Identity-Level Privacy Guarantees for Images

DGX agent

arXiv:2608.17147v1 Announce Type: cross Abstract: Image-to-image face generators are widely used, and visual dissimilarity between their outputs and source images is sometimes treated as evidence of p

model-releasesarxiv-cs-lg

19 Aug 2026

Plug-and-Play Traffic Element Awareness for End-to-End Autonomous Driving

arXiv:2608.18035v1 Announce Type: new Abstract: Traffic elements such as traffic lights and road signs play a fundamental role in human driving decisions and should naturally influence end-to-end driv

Policy Optimization and Statistical Inference for Online Contextual Matrix Games

arXiv:2608.17173v1 Announce Type: cross Abstract: Online decision making often requires navigating a landscape shaped by both dynamic contexts and strategic interactions. In competitive pricing, for e

PRISM: Precision and contact-rich Real-world Industrial Skill dataset with Multimodal sensing

model-releasesarxiv-cs-ro

arXiv:2608.17962v1 Announce Type: new Abstract: Recent progress in robotic learning has been fueled by large-scale datasets collected in everyday environments. However, most existing datasets emphasiz

Probing the Prefill: Detecting Code Vulnerabilities via Latent Activations

arXiv:2608.16970v1 Announce Type: cross Abstract: LLM-based code generation is now embedded in mission-critical pipelines, but defenses against vulnerable output remain post-hoc -- static analyzers, f

PTXBench: Benchmark and Adapt LLMs for GPU Kernel Optimization with Architecture-specific PTX

arXiv:2608.17379v1 Announce Type: cross Abstract: We introduce PTXBench, a benchmark for evaluating and adapting large language models (LLMs) to use architecture-specific PTX for GPU kernel optimizati

Q-Interference: Memory-Efficient Phase-Aware Quantum-Inspired Attention

arXiv:2608.17288v1 Announce Type: new Abstract: GPT attention measures token compatibility through dot-product similarity. This mechanism is simple, effective, and memory-efficient. But it does not ex

Rapid Debris-Volume Estimation from Post-Hurricane Aerial Imagery

arXiv:2608.17165v1 Announce Type: new Abstract: Hurricane debris removal is planned, contracted, and federally reimbursed on the basis of volume estimates, yet operational practice still relies on par

Reflex-Guard: A Low-Latency Guardrail for LLM Prompt Safety Using Dense Semantic Embeddings

arXiv:2608.17556v1 Announce Type: cross Abstract: Large Language Models (LLMs) in real-world applications often face the risks of specially crafted prompts designed to bypass the safety controls. Exis

RoBell-RVFL: A Robust Generalized Bell Random Vector Functional Link Network

arXiv:2608.16965v1 Announce Type: new Abstract: The dominance of majority classes in real-world datasets poses a fundamental challenge to randomized neural networks, often biasing decision boundaries

S^3AM: A Single-Stream SAM with Reliability-Calibrated Frequency Adapter for Multi-modal Salient Object Detection

arXiv:2608.17475v1 Announce Type: new Abstract: Vision foundation models have recently advanced multi-modal salient object detection (MSOD) through parameter-efficient tuning and prompt learning. Howe

Scanline-Aware Animatable Gaussian Avatars from Rolling-Shutter Videos

arXiv:2608.17314v1 Announce Type: new Abstract: Animatable human avatars are routinely reconstructed from multi-view video under a silent assumption: that every pixel of a frame observes the same inst

SCENARIODIFF: A Scenario-level Guidance Framework for Multimodal Time Series Forecasting--Extended Version

arXiv:2608.17164v1 Announce Type: new Abstract: Textual context such as news, reports, and logs can provide valuable signals for time series forecasting, especially when future dynamics are driven by

SE-MoLoRA: Shared-Expert LoRA Adapters for Domain-Specific Photographic Assessment

arXiv:2608.17514v1 Announce Type: new Abstract: Vision-language models can describe images fluently, but they often fail to provide actionable photographic critique because semantic content and aesthe

SFMformer: A Spatial-Frequency Modulation Transformer for Lightweight Image Super-Resolution

arXiv:2608.17966v1 Announce Type: new Abstract: Sparse attention mechanisms, which score all token pairs but propagate only the strongest, now underpin the most efficient Transformers for lightweight

SIGMA: SHAP-Guided Implicit-Trajectory Generation for Metadata-Free LLM-Based AutoFE

arXiv:2608.17948v1 Announce Type: cross Abstract: Recent research has leveraged Large Language Models (LLMs) to enhance Automated Feature Engineering (AutoFE) through semantic descriptions and traject

SignalReasoner: Assessing the Upper Bound of 3B Models for Signal Mathematical Reasoning

arXiv:2608.17301v1 Announce Type: new Abstract: Post-training with supervised chain-of-thought fine-tuning and reinforcement learning from verifiable rewards has substantially improved the mathematica

SPSA Hyperparameter Tuning for Variational Quantum Natural Language Inference

arXiv:2608.16939v1 Announce Type: cross Abstract: Training variational quantum models requires choosing between parameter-shift gradients, which are exact but cost O(P) forward evaluations, and simult

StagedWorkspace: A Versioned Workspace for Knowledge-Work Agents

arXiv:2608.18050v1 Announce Type: new Abstract: AI agents increasingly perform knowledge work (i.e., produce and modify persistent digital artifacts such as code repositories, documents, spreadsheets,

StartupBench: Benchmarking General-Purpose Agents on Market-Validated End-to-End Workflows

arXiv:2608.17800v1 Announce Type: new Abstract: Recent advances in Large Language Models(LLMs) and agents have substantially improved the ability of AI systems to execute complex tasks. Yet existing b

Structural Plan-to-Model Conversion with Deterministic Geometry and Guarded Agentic Vision-Language Refinement

arXiv:2608.17237v1 Announce Type: cross Abstract: Converting structural framing plans into editable finite-element model drafts remains labor-intensive and prone to transcription error. Existing drawi

Supporting Calibrated Reliance in Human-AI Collaboration: Different Strategies for Different Tasks

arXiv:2604.03237v2 Announce Type: replace-cross Abstract: As AI systems increasingly support human decision making, a central challenge is determining what information helps people recognize when to r

SW-ProxyCE: Zero-Query Adversarial Transfer from Public EEG Encoders to Private Downstream Models

arXiv:2608.16931v1 Announce Type: new Abstract: Electroencephalography (EEG) foundation models have recently emerged as a promising paradigm for EEG decoding by learning reusable representations from

Temporal Leakage in Financial News NLP: A Multi-Architecture Audit with a Regime-Specific M&A Signal

arXiv:2608.17223v1 Announce Type: new Abstract: Financial-news direction prediction has become a popular NLP benchmark, yet reported gains depend critically on whether the train-test split is chronolo

The 10th AI City Challenge

arXiv:2608.17044v1 Announce Type: cross Abstract: The 10th AI City Challenge, held with ECCV 2026, marks a decade of community benchmarking for intelligent transportation, smart cities, and physical A

The IOL-AI Challenge: An Open Challenge towards Advancing Linguistic Reasoning

arXiv:2608.18011v1 Announce Type: new Abstract: Reasoning in LLMs is overwhelmingly studied in domains that provide a model with rules: mathematics and code. Linguistic puzzles invert this: the solver

Thinking in a Low-Resource Language: What SFT Builds, What RL Fixes, What Accuracy Cannot See

arXiv:2608.17744v1 Announce Type: new Abstract: Take three frontier mixture-of-experts models (Alibaba, OpenAI, NVIDIA; 3.6-4.0B active parameters each) and fine-tune them to reason in a low-resource

Tight Bounds for Data-driven Multiple Hyper-parameter Tuning with Structured Loss Function

arXiv:2608.17343v1 Announce Type: new Abstract: Data-driven algorithm design frames hyperparameter tuning as a statistical learning problem, but establishing generalization guarantees remains challeng

TileMix: Tile-Centric Mixed-Precision Attention for LLM Inference Acceleration

arXiv:2608.17336v1 Announce Type: new Abstract: Long-context prefill in large language models (LLMs) incurs substantial computation and memory traffic because dense self-attention computes quadratic q

Token Optimization and Context Window Management in Multi-Agent AI Workflows

arXiv:2608.17188v1 Announce Type: cross Abstract: Multi-agent AI workflows are limited not only by model quality but by token cost, latency, and context-window quality. This paper presents a practitio

Too Sure to Be Safe: Model Calibration for Reliable Log Anomaly Detection

arXiv:2608.17965v1 Announce Type: cross Abstract: Online log anomaly detection is critical for maintaining the reliability of large-scale computing systems. Although recent language model-based log an

TRUSS: Towards Task-Reliable and User-Safe Automated Agent Skill Generation

arXiv:2608.17588v1 Announce Type: new Abstract: Agent Skills package reusable natural language procedures with executable resources, enabling software agents to acquire task specific capabilities with

TSQueryBench: LLM-as-a-Judge for Time Series Explanations

arXiv:2604.02118v2 Announce Type: replace Abstract: Natural language explanations of time series data are increasingly produced by foundation models in high stakes domains, making factual correctness

Vision-Language Models for Analog Gauge Reading: An Empirical Study of Specialization, Transfer and Reliability

arXiv:2608.17723v1 Announce Type: new Abstract: Analog gauges remain common in industrial environments where manual inspection is costly or hazardous. The engineering application addressed here is dir

What Aggregate Scores Miss: Measuring Item-Level Regressions in Commercial LLM API Migrations

arXiv:2608.17719v1 Announce Type: cross Abstract: Context: Software systems that depend on commercial large language model APIs must migrate to successor versions when vendors deprecate older models.

When Personalization Becomes Bias: Structural and Discursive Religious Framing in AI-Generated Financial Advice

arXiv:2608.16909v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly integrated into financial advisory systems, yet their role in reproducing religious bias remains underex

When to Review: Spaced Repetition for Continual Pre-Training of Language Models

arXiv:2608.17530v1 Announce Type: new Abstract: Continual pre-training of large language models must acquire new information without erasing old knowledge. Existing replay methods often choose a globa

When Writing Style Drifts: Benchmarking Authorship Verification under Distribution Shifts in Genre, Time and the AI-Era

arXiv:2608.17979v1 Announce Type: new Abstract: Authorship verification (AV) assumes that an author's writing style remains sufficiently stable to distinguish it from that of other writers. In practic

Which Source Wins? Task-Dependent Reliance in Vision-Language Models

arXiv:2608.17205v1 Announce Type: new Abstract: Vision-language models (VLMs) combine images and text, but when the two conflict and one becomes harder to read, it is unclear how a model shifts its re

WorldBench: Benchmarking Physical Understanding of World Models by Isolating Physics Concepts

arXiv:2601.21282v2 Announce Type: replace Abstract: Recent advances in generative foundational models, often termed 'world models,' have propelled interest in applying them to critical tasks like robo

Wuying-Browser-Agent: Real-World Centric Fundamental Long-Horizon Browser Agents

arXiv:2608.17319v1 Announce Type: new Abstract: Browser agents perform well on short, clean demonstrations, but real deployment is fundamentally different: agents must sustain dozens of decisions on l

A Comprehensive Survey of Wireless Foundation Models for AI-Native 6G Networks

arXiv:2608.14694v1 Announce Type: new Abstract: Foundation models are emerging as a transformative paradigm for AI-native sixth-generation (6G) wireless networks by enabling scalable, transferable, an

A Large-Scale Chinese Knowledge Graph-Text Alignment Dataset for Benchmarking Knowledge-Grounded LLMs

arXiv:2510.06039v2 Announce Type: replace-cross Abstract: Reliable evaluation of knowledge-grounded Large Language Models (LLMs) in Chinese requires resources that explicitly align Chinese-language te

A Machine-Learned Comorbidity Index

arXiv:2606.17450v2 Announce Type: replace Abstract: Traditional comorbidity scores (e.g., Charlson and Elixhauser) are widely used for risk adjustment and patient stratification, but they have two key

A Parameter-Free Few-Shot Evaluation for Elephant Vocalisation Classification

arXiv:2608.14824v1 Announce Type: cross Abstract: We present a parameter-free episodic evaluation of nearest-centroid classification for elephant vocalisations on fixed pretrained acoustic embeddings,

A Policy Algebra for Trust-Preserving Agentic AI Execution

arXiv:2608.16402v1 Announce Type: new Abstract: Large language model-based agentic frameworks primarily optimize capability: whether an agent can reason, retrieve information, call tools, delegate wor

A Scalable Pipeline for LLM-Teacher Distillation Labeling: Work-Stealing Job Scheduling and Memory-Aware GPU Concurrency

arXiv:2608.15975v1 Announce Type: cross Abstract: Labeling large text corpora with LLM teachers has become a practical route to training data at scale. At millions of items, hand-labeling every batch