Search: “model-releases”

Unlearning at Scale: State-Exact Trace-Preserving Deletion in Billion-Parameter Language Models

arXiv:2508.12220v2 Announce Type: replace-cross Abstract: Can a prospectively instrumented training continuation reproduce a deletion counterfactual exactly after selected examples leave its replay da

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Model Releases

Vero: Can AI Agents Build Formally Verified Software Repositories?

DGX agent

arXiv:2608.13522v1 Announce Type: cross Abstract: AI agents are increasingly used for programming, but do not provide any guarantee on the correctness of generated code. Verified code generation, in w

model-releasesarxiv-cs-ai

14 Aug 2026

Virtual Temperature Sensors in Power Transformers Using Neural Ordinary Differential Equations

arXiv:2608.13260v1 Announce Type: new Abstract: Accurate modeling and forecasting of power transformer thermal behavior are critical for reliability, asset lifetime, and optimized power system operati

Vision-Language Models are Fragile Multilingual Associators

arXiv:2608.12333v1 Announce Type: cross Abstract: Vision-language models must associate visual entities with textual attributes. Whether these associations or concept bindings remain stable when the l

Wasserstein Filtering: A Sample Selection Method for Robust Distribution Learning

arXiv:2608.13418v1 Announce Type: cross Abstract: Given a dataset where a portion of the samples are contaminated, our goal is to recover the underlying clean population distribution. To this end, we

When AI Is Your Pastor: A Benchmark for Theological Triage and Pastoral Guidance in Large Language Models

arXiv:2608.12324v1 Announce Type: cross Abstract: People increasingly ask large language models (LLMs) for counsel on questions of faith, doctrine, and pastoral care. These questions are not ordinary

When Can You Trust Offline Evaluation of Equal-Cost Top-k Allocation? A Controlled, Reproducible Benchmark and Practitioner's Guide

arXiv:2608.12489v1 Announce Type: new Abstract: Organizations decide whom to treat under a budget and want to know what a targeting rule would have earned before deploying it. Off-policy evaluation pr

When Large Language Models are More PersuasiveThan Incentivized Humans, and Why

arXiv:2505.09662v4 Announce Type: replace Abstract: Large Language Models (LLMs) have been shown to be highly persuasive, but when and why they outperform humans is still an open question. We compare

When Your Agent Opens the Chat App: Agent-Controlled Search over Raw Chat Logs Rivals Structured Memory

arXiv:2608.12888v1 Announce Type: new Abstract: Agent-memory systems increasingly buy retrieval quality with structure, transforming raw conversation histories into summaries, embeddings, trees, or kn

Where Should Optimizer State Live? Tiered State Allocation for Memory-Efficient Mixture-of-Experts Training

arXiv:2607.19058v2 Announce Type: replace-cross Abstract: Optimizer state is the largest single line item in the memory budget of mixture-of-experts (MoE) training. On a 6.78B-parameter MoE language m

Where You Measure Decides What You Measure: Position Selection in Ablation-Based SAE Evaluation

arXiv:2608.13337v1 Announce Type: new Abstract: Sparse autoencoders are meant to name the things a language model computes, and the usual way to check that a latent matters is to switch it off and see

Which LLM Is Your Ideal Companion? Evaluating Emotional Companion Capabilities of LLMs Based on Adult Attachment Theory

arXiv:2608.13168v1 Announce Type: new Abstract: As large language models (LLMs) are increasingly applied for emotional companionship, evaluating their behavior and capabilities in intimate relationshi

Why Do AI Agents Break Rules? How Framing, Context, and Social Signals Shape Compliance

arXiv:2608.12323v1 Announce Type: cross Abstract: Specifying a penalty can paradoxically convert a legal obligation into a cost-benefit calculation that favors violation. We demonstrate that this enfo

A Cascaded Unsupervised-Supervised NLP Pipeline for Detecting Accusatory Language in Public Procurement

arXiv:2608.12269v1 Announce Type: new Abstract: Public procurement involves the allocation of substantial financial resources; therefore, continuous oversight through audits, controls, and monitoring

A comparison of CNN architectures for Alzheimer's disease detection in single-view MRI scans

arXiv:2608.11762v1 Announce Type: cross Abstract: Alzheimer's disease is a leading cause of death with no cure. Therefore, early detection is critical to slow progression and preserve quality of life.

A corpus-specific clinical RAG system matches or outperforms newer frontier LLMs on HealthBench

arXiv:2608.12138v1 Announce Type: cross Abstract: General-purpose large language models (LLMs) have recently been reported to match or exceed specialized clinical AI tools on medical benchmarks, but s

A Local Sinkhorn Framework for Conditional Distribution Reconstruction of Multidimensional Random Fields

arXiv:2608.11613v1 Announce Type: new Abstract: In this paper, we propose a local Sinkhorn divergence framework for conditional distribution reconstruction of multidimensional random fields. By utiliz

A Neighborhood Attention Transformer Network for Enhanced 3D Segmentation of the Left Anterior Descending Artery

arXiv:2608.12274v1 Announce Type: cross Abstract: Background: Accurate segmentation of the Left Anterior Descending (LAD) artery in 3D free-breathing, non-contrast CT is critical for cardiac dose spar

A Variational Analysis of Kernel Learning with Learnable Linear Transformations

arXiv:2502.11665v3 Announce Type: replace-cross Abstract: The classical kernel ridge regression problem aims to find the best fit for the output Y as a function of the input data Xin R^d, with a fixed

ADEPT: A Unified Framework for Deep Learning Test Adequacy

arXiv:2608.12144v1 Announce Type: cross Abstract: Over the past decade, many test adequacy metrics have been proposed for deep learning that characterize test dataset adequacy from different perspecti

Advancing MLLM-based UAV Image Understanding and Reasoning: A Benchmark and a Training-Free Multi-Agent System

arXiv:2608.11738v1 Announce Type: cross Abstract: Multimodal Large Language Model (MLLM)-based UAV aerial image understanding and reasoning is essential for aerial intelligence yet poses distinct chal

Agent Safety Should Be a Runtime Contract

arXiv:2608.11274v1 Announce Type: cross Abstract: The dominant paradigm treats AI safety as a property to be instilled during model training via RLHF, DPO, or Constitutional AI. We argue this is struc

AgenticTwin: An Agentic LLM Framework Integrated with Digital Twin for Anomaly Detection

arXiv:2608.11679v1 Announce Type: new Abstract: Digital twins are increasingly used to monitor and simulate the behavior of cyber-physical systems. Even with skilled operators, interpreting anomalies

AI4AI at Test-Time: Strong-to-Weak Capability Transfer via Harnesses

arXiv:2608.12307v1 Announce Type: cross Abstract: Recent work on distillation transfers the capabilities of large models to smaller ones often by updating the latter's parameters, through teacher forc

Air Quality Station Simulation via LSTM and Attention-Based Modelling

arXiv:2608.11839v1 Announce Type: new Abstract: Poor air quality in urban areas is driven by a complex chain of processes and presents a significant public health concern. To better understand and con

An Agentic Workflow for Legacy HPC Modernization: Converting the Two-Electron-Integral Core of GAMESS

arXiv:2608.12249v1 Announce Type: new Abstract: Modernizing legacy Fortran is a problem of volume: the transformations are individually routine, but the codebases can be enormous, and across much of c

Analysis of Federated Aggregation under Model Poisoning and Backdoor Attacks: A Reconstructed Cross-Dataset and Cross-Architecture Benchmark

arXiv:2608.11423v1 Announce Type: cross Abstract: Robust comparisons of federated aggregation methods require joint consideration of predictive performance, threat definitions, metric semantics, and e

Apodex Discovery: Reality Benchmarks and Environments for Evaluating and Building Discoverative Artificial Intelligence

arXiv:2608.11341v1 Announce Type: new Abstract: Apollo did not reach the Moon merely because its engineers could solve difficult equations. It succeeded by turning a distant ambition into a mission ar

Auditing Frame-Level AUC in Weakly Supervised Video Anomaly Detection: Granularity, Resolution, and Scene Bias

arXiv:2608.11985v1 Announce Type: new Abstract: Frame-level area under the ROC curve (AUC) is the dominant evaluation metric for weakly supervised video anomaly detection (WSVAD). Its standard form me

Automated binary classification of hazelnut X-ray images: A deep-learning benchmark for quality assessment

arXiv:2608.11759v1 Announce Type: new Abstract: Non-destructive X-ray imaging can reveal internal hazelnut defects that are difficult to detect by external inspection alone; however, automated interpr

AutoWorldModel-Bench: A State-Centric Benchmark for Automated World-Model Research

arXiv:2608.11216v1 Announce Type: new Abstract: World modeling is an unsettled field: architectures, training objectives, and state representations interact in complex ways, and no single recipe domin

AVA-Encoder: Towards Agent-Native Video Representation Learning

arXiv:2608.12313v1 Announce Type: cross Abstract: Creative agents still lack an effective way to learn from high-quality human films, limiting their ability to produce cinematic-grade videos. A key ch

Avatar-Forever: Decoupled Parallel Training for High-Quality Real-Time Infinite Avatars

arXiv:2608.12107v1 Announce Type: new Abstract: Existing streaming video systems often rely on sequential, distillation-centered training pipelines to enable few-step long-video generation. However, t

AWARe: Mitigating Catastrophic Forgetting via Activation-Weighted Adaptive REtention

arXiv:2608.11758v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) exhibit strong generalization and reasoning abilities due to large-scale multimodal pre-training. However, fine

Backtrader-Bench: Benchmarking LLM Agents on Algorithmic Trading with Self-Generated MCQs

arXiv:2608.11232v1 Announce Type: cross Abstract: Evaluating LLM coding agents in algorithmic trading is difficult because static benchmarks risk data contamination and numerical backtest outputs requ

Behavior and Representation in Open-Weight Large Language Models for Combinatorial Optimization: From Feature Extraction to Algorithm Selection

arXiv:2512.13374v2 Announce Type: replace Abstract: Recent advances in Large Language Models (LLMs) open new perspectives for automation in optimization, yet little is known about whether their intern

Benchmark-Based Comparative Assessment of Publicly Benchmarked Indian Foundation Models: A Capability and Evaluation-Maturity Framework

arXiv:2608.11891v1 Announce Type: cross Abstract: Governments increasingly fund indigenous foundation models to strengthen national AI capability, digital sovereignty, and multilingual computing. Asse

Benchmarking Cyberattack Detection in Electric Vehicle Charging Infrastructure with Benign User Updates

arXiv:2608.11286v1 Announce Type: cross Abstract: Cyberattack detection in electric vehicle charging infrastructure is complicated by legitimate post-activation revisions to requested energy and depar

Benchmarking LLM Judges for Mobile Agent Evaluation

arXiv:2608.11434v1 Announce Type: new Abstract: Mobile agent benchmarks increasingly rely on LLM-based judges to evaluate task completion, yet the reliability of these judges on mobile agent trajector

Beyond Parameter Space: NTK-Guided Personalized Aggregation for Robust Federated Learning

arXiv:2608.12108v1 Announce Type: new Abstract: Federated learning (FL) enables collaborative model training across distributed clients while keeping data local. A central challenge is determining whi

Beyond Trial-and-Error: Agentic Optimization for Image-to-Video Adherence

arXiv:2608.12290v1 Announce Type: cross Abstract: Modern black-box Image-to-Video (I2V) models offer powerful capabilities in automated content creation, yet their lack of fine-grained control and rel

BrowseSafe: Understanding and Preventing Prompt Injection Within AI Browser Agents

arXiv:2511.20597v2 Announce Type: replace-cross Abstract: The integration of artificial intelligence (AI) agents into web browsers introduces security challenges that go beyond traditional web applica

Can Frontier LLMs Match Natively Multimodal Embeddings? A Comparison on Hard-Negative Text-to-Image Retrieval

arXiv:2608.11343v1 Announce Type: new Abstract: Multimodal retrieval and classification across different types of media, spanning text, images,video and audio, has traditionally relied on dual-encoder

Causal Agent based on Large Language Model

arXiv:2408.06849v3 Announce Type: replace Abstract: The large language model (LLM) has achieved significant success across various domains. However, the inherent complexity of causal problems and caus

Causal inference for group-contaminated structured outcomes: observable quotients, lossless reduction and exact randomization inference

arXiv:2608.11954v1 Announce Type: cross Abstract: Structured potential outcomes such as microscopy images may be recorded after an unknown, unit-specific transformation. If that transformation can dep

Causal Structure is Inducible but Functionally Decoupled: The Routing/Readout Boundary of a Typed Mechanism Library

arXiv:2608.11767v1 Announce Type: new Abstract: When a language model answers an interventional question, the computation it must perform depends on the type of evidence the query requires. We report

CoDiR: Confidence-Guided Diffusion Refinement for Semi-Supervised Histopathology Segmentation

arXiv:2608.11807v1 Announce Type: new Abstract: Semi-supervised histopathology segmentation is challenging due to scarce annotations and unreliable pseudo-labels in ambiguous gland regions. To address

COGENT: Counterfactual Gaussian Explanations for Volumetric Medical Images

arXiv:2608.11422v1 Announce Type: new Abstract: Explainability is essential for deploying deep learning models in high-stakes medical applications. Existing explainability methods for volumetric imagi