Search: “concepts”

INSPIRE: An Internalize-Then-Improve Approach for Example-Driven Mathematical Reasoning

arXiv:2608.27501v1 Announce Type: new Abstract: Mathematical reasoning has seen rapid progress in large language models (LLMs), yet existing methods optimize predominantly for final-answer correctness

safetyarxiv-cs-cl

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Post-Training VLMs for Video Mistake Detection

DGX agent

arXiv:2608.28406v1 Announce Type: new Abstract: Human mistakes are inevitable when following instructions, yet they can lead to severe consequences. As such, there has been an increased interest in de

model-releasesarxiv-cs-cv

31 Aug 2026

Prompt-Guided Interactive Segmentation of Interstitial Lung Disease in Thoracic CT

arXiv:2608.28453v1 Announce Type: new Abstract: Accurate segmentation of interstitial lung disease (ILD) patterns is essential for quantitative disease assessment and longitudinal monitoring. However,

researcharxiv-cs-cv

Relational Knowledge Distillation Brings DNN Representations Close Enough to Humans to Be Aligned Without Supervision

arXiv:2608.27877v1 Announce Type: new Abstract: Linking the internal representations of deep neural networks (DNNs) to human mental representations is important for using DNNs as computational models

safetyarxiv-cs-cv

Local Ai

RiskBlend: A Multi-Signal Framework for Test Input Prioritization in Machine Learning Regression Testing

arXiv:2608.27704v1 Announce Type: new Abstract: When machine learning classifiers are retrained, inputs correctly classified by the previous model version may be misclassified by the updated version,

local-aiarxiv-cs-lg

Local Ai

TACIT-Switch: Cost-Aware Model Escalation for LLM Agents from Censored Supervision

arXiv:2608.27911v1 Announce Type: new Abstract: Agents with smaller language-model backbones are less expensive but can drift into persistent failure modes, whereas those with larger backbones are gen

local-aiarxiv-cs-lg

Local Ai

When the City Teaches the Car: Label-Free 3D Perception from Infrastructure

arXiv:2603.16742v2 Announce Type: replace Abstract: Building robust 3D perception for self-driving still relies heavily on large-scale data collection and manual annotation, yet this paradigm becomes

local-aiarxiv-cs-cv

AI Revealed Preferences

model-releasesarxiv-cs-ai

arXiv:2608.26178v1 Announce Type: new Abstract: There is growing interest in whether language models have stable preferences, for technical, safety, and philosophical reasons. We test 20 language mode

Counterfactual Bias Testing for Application Tracking System

arXiv:2608.26899v1 Announce Type: new Abstract: Automated candidate-job matching systems are increasingly classified as high-risk AI under emerging regulation, yet auditing them for demographic bias i

How Language Models Organize and Structure Moral Knowledge

arXiv:2608.27402v1 Announce Type: cross Abstract: How do large language models (LLMs) organize moral knowledge? Models detect moral content broadly, but detection is a low bar. We ask whether they go

Token-Level Advertising

arXiv:2608.27382v1 Announce Type: cross Abstract: Generative AI is transforming how people access information, challenging traditional advertising mechanisms built around predefined slots. Towards gen

applicationsarxiv-cs-lg

Why did My Robot Just Change Personality? Prompting Guidelines for a Grounded Robot Persona in LLM-Based HRI

arXiv:2608.26182v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for verbal interaction in social robots, yet prompt design in human-robot interaction (HRI) remains u

Advancements in Content-Based Image Retrieval: A Comprehensive Survey of Relevance Feedback Techniques

arXiv:2312.10089v2 Announce Type: replace Abstract: Content-based image retrieval (CBIR) systems have emerged as crucial tools in the field of computer vision, allowing for image search based on visua

researcharxiv-cs-cv

Demystifying Reinforcement Learning Post-Training of Language Models

arXiv:2608.24949v1 Announce Type: cross Abstract: Reinforcement learning (RL) post-training has emerged as a powerful framework for enhancing the capabilities of large language models (LLMs), enabling

safetyarxiv-cs-cl

Drift Variation Autoencoder: Unifying Generation and Representation Learning through Conditional Posterior Flow Matching

model-releasesarxiv-cs-lg

arXiv:2608.25138v1 Announce Type: new Abstract: Stochastic masking, cropping, or modality removal makes deterministic reconstruction an incomplete target: one observation can admit many clean completi

Finding and using interpretable latents in a neutrino foundation model with sparse autoencoders

arXiv:2608.26090v1 Announce Type: cross Abstract: We present a first application of sparse-autoencoder-based mechanistic interpretability to particle physics. Studying a neutrino foundation model pret

researcharxiv-cs-lg

FuzzingBrain-Bench V1: Evaluating Open-Ended Bug Discovery by LLMs

model-releasesarxiv-cs-lg

arXiv:2608.25158v1 Announce Type: cross Abstract: Evaluating the ability of large language models (LLMs) to discover software bugs is increasingly important. Existing benchmarks typically evaluate thi

Learning to Detect Unseen Jailbreak Attacks in Large Vision-Language Models

arXiv:2508.09201v5 Announce Type: replace-cross Abstract: Despite extensive alignment efforts, Large Vision-Language Models (LVLMs) remain vulnerable to jailbreak attacks. To mitigate these risks, exi

safetyarxiv-cs-cv

Model-Agnostic Open-Set Air-to-Air Visual Object Detection for Reliable UAV Perception

model-releasesarxiv-cs-cv

arXiv:2509.09297v2 Announce Type: replace Abstract: Open-set detection is crucial for robust UAV autonomy in air-to-air object detection under real-world conditions. Traditional closed-set detectors d

MTDiag: A Multi-Turn Diagnostic Dataset Towards Clinically Meaningful LLM Evaluation

arXiv:2608.25085v1 Announce Type: new Abstract: Clinical diagnosis is fundamentally interactive and incremental, yet the dominant paradigm for evaluating Large Language Models (LLMs) in medicine remai

agentsarxiv-cs-cl

Trojan Attacks on Neural Network Controllers for Robotic Systems

arXiv:2602.05121v3 Announce Type: replace-cross Abstract: Neural network controllers are increasingly deployed in robotic systems for tasks such as trajectory tracking and pose stabilization. However,

applicationsarxiv-cs-ro

What Do Medical Vision-Language Models Learn in Radiology? Transfer, Alignment, and Source-Proxy Leakage Under Distribution Shift

arXiv:2608.25251v1 Announce Type: new Abstract: Medical vision-language models (VLMs) can appear reliable in-domain while failing when acquisition domain, paired supervision, or evaluation protocol ch

safetyarxiv-cs-cv

Tutorials

A Behavior-Guided Online Probabilistic Forecasting Method for Electric vehicle Charging Loads

arXiv:2608.24441v1 Announce Type: new Abstract: Electric vehicle (EV) charging loads exhibit strong behavioral heterogeneity and temporal variability, posing significant challenges for online probabil

tutorialsarxiv-cs-ai

Beyond the Mandate: A Systematic Security Analysis of the Agent Payments Protocol (AP2)

arXiv:2608.23858v1 Announce Type: cross Abstract: The Agent Payments Protocol (AP2), introduced by Google, enables large language model (LLM)-driven shopping agents to authorize and execute payments o

agentsarxiv-cs-ai

Incorporating Cognitive Load and Knowledge Transfer for Multi-Domain Knowledge Tracing

arXiv:2608.24005v1 Announce Type: new Abstract: Knowledge Tracing (KT) aims to assess students' dynamic knowledge states from their learning histories. While most existing KT methods focus on single-d

applicationsarxiv-cs-ai

Lifted Model Construction under Approximate Commutativity

arXiv:2608.24713v1 Announce Type: new Abstract: Lifted inference algorithms enable scalable probabilistic inference even for large object domains by leveraging the indistinguishability of objects in a

ReGround-Surg: Reliability-Guided Anchor Grounding for Referring Surgical Video Segmentation

arXiv:2608.24671v1 Announce Type: new Abstract: Referring surgical video segmentation requires segmenting a target instrument or tissue region across video frames according to a natural language expre

researcharxiv-cs-cv

Resilience Matters for Embodied Agents System: New Metrics, Systematic Evaluation, and Optimization

arXiv:2608.23839v1 Announce Type: cross Abstract: Embodied Agents System (EAS) are increasingly deployed in open-world physical domains, where reliability directly dictates deployment quality and huma

A Survey Instrument to Assess Students' AI and Generative AI Knowledge

arXiv:2608.21391v1 Announce Type: cross Abstract: In this research-to-practice paper we present a survey that can be used to assess students' AI knowledge. As the use of artificial intelligence (AI),

applicationsarxiv-cs-ai

Agentic AI for Safety-critical Multi-drone Systems: Challenges and Opportunities

arXiv:2608.21444v1 Announce Type: new Abstract: Multi-drone systems are increasingly positioned for safety-critical missions such as search and rescue (SAR) and critical infrastructure monitoring. Yet

Agentic Scaffolding Amplifies Sycophantic Behavior in Large Language Models

arXiv:2608.21377v1 Announce Type: cross Abstract: Sycophancy in large language models, the tendency to prioritize user agreement over truthful responses, has been documented extensively but studied pr

agentsarxiv-cs-ai

Beyond Benchmarking: Scenario-Based Evaluation of Large Language Models for Personalized Learning

model-releasesarxiv-cs-ai

arXiv:2509.05346v3 Announce Type: replace Abstract: While large language models (LLMs) are increasingly being adopted to support personalized learning, there remains limited understanding of how their

Beyond Benchmarks: LLM Evaluation with an Anthropomorphic and Lifecycle-oriented Roadmap

model-releasesarxiv-cs-ai

arXiv:2508.18646v3 Announce Type: replace Abstract: Despite their rapid advancement, large language models (LLMs) suffer from a critical disconnect between benchmark scores and real-world utility. Cur

CyberFactory: Scaling Cyber Security Capabilities with Instances from the Wild

model-releasesarxiv-cs-cl

arXiv:2608.23181v1 Announce Type: cross Abstract: As large language models (LLMs) continue to advance in coding capabilities, their potential in cybersecurity has drawn increasing research attention,

Deep Learning-Driven Inverse Design of Doherty Power Amplifiers Using Pixelated Combiners and Dual-State Impedance Synthesis

arXiv:2606.18395v2 Announce Type: replace-cross Abstract: The output combiner of a Doherty power amplifier (PA) integrates load modulation, impedance matching, and phase compensation within a single n

DIAG: Diagnostic Iterative Alignment and Generation for Data-Efficient Mathematical Preference Distillation

arXiv:2608.22806v1 Announce Type: new Abstract: Iterative preference optimization is essential for aligning Large Language Models on mathematical reasoning tasks, yet its efficiency is often throttled

safetyarxiv-cs-cl

Dual-Grained Agent Memory and Shapley Context Attribution for Multimodal Agentic Learner

model-releasesarxiv-cs-cv

arXiv:2608.23268v1 Announce Type: new Abstract: Frontier multimodal large language models (MLLMs) deliver impressive perception yet still falter on scientific and mathematical reasoning. Parameter-lev

Figurative Justice: Detecting metaphors in Hindi judgements with qualitative assessment and transformers

arXiv:2608.22446v1 Announce Type: new Abstract: Metaphors are figurative use of words for conceptual mapping. Metaphor detection in the legal context has been crucial as metaphors are persuasive jurid

applicationsarxiv-cs-cl

Hybrid Panels: Toward Human-AI Collaboration in Survey Research

arXiv:2608.22582v1 Announce Type: cross Abstract: Large-scale population surveys are essential for generating robust social and scientific insights, yet they face significant challenges, including dec

MOCLIP: A Foundation Model for Large-Scale Nanophotonic Inverse Design

arXiv:2511.18980v2 Announce Type: replace-cross Abstract: Foundation models (FM) are transforming artificial intelligence by enabling generalizable, data-efficient solutions across different domains f

More accurate behavioral predictions with hybrid Bayesian-connectionist models

arXiv:2608.22154v1 Announce Type: new Abstract: Researchers must often choose between Bayesian or neural network models of behavior, two paradigms with complementary strengths and weaknesses. An ideal

researcharxiv-cs-lg

Neural Boltzmann Equations

model-releasesarxiv-cs-lg

arXiv:2608.23022v1 Announce Type: cross Abstract: The dynamics of particles in the early universe are described by Boltzmann equations, which involve high-dimensional phase-space integrals. Classical

Retrieval-Augmented Visual Prompting: Guiding Foundation Models in Two-Photon Imaging

model-releasesarxiv-cs-cv

arXiv:2608.21970v1 Announce Type: new Abstract: Two-photon calcium imaging presents a challenging setting for foundation models: image appearance varies substantially across recordings and experimenta

Robustness of IR Models to Collection Growth

arXiv:2608.23419v1 Announce Type: cross Abstract: Information Retrieval (IR) systems seek to identify relevant documents within a collection. In practical applications, collections are dynamic, with d

researcharxiv-cs-cl

Using Wavelet Domain Fingerprints to Improve Source Camera Identification

arXiv:2507.01712v2 Announce Type: replace Abstract: Camera fingerprint detection plays a crucial role in source identification and image forensics, with wavelet denoising approaches proving particular

applicationsarxiv-cs-cv

XIT: Exploration and Exploitation Informed Trees for Active Gas Distribution Mapping in Unknown Environments

arXiv:2602.13739v2 Announce Type: replace Abstract: Mobile robotic gas distribution mapping (GDM) provides critical situational awareness during emergency responses to hazardous gas releases. However,

agentsarxiv-cs-ro

Auditable by Construction: An Ontology-Driven Framework for Trustworthy LLM Analytics in Enterprise Finance

arXiv:2608.20661v1 Announce Type: new Abstract: Enterprise adoption of large language models in finance is constrained less by fluency than by trust: in Financial Planning and Analysis (FP&A) and othe

applicationsarxiv-cs-ai

24 Aug 2026

Inhibitory Attention for Clinical Long-Context Reasoning: Characterizing and Mitigating Lost-in-the-Middle Effects in EHR Processing

arXiv:2608.20348v1 Announce Type: cross Abstract: Electronic health records now routinely exceed 100,000 tokens per patient. Yet large language models exhibit the lost-in-the-middle (LitM) effect: inf