Search: “papers”

Vibe Coding Ate My Homework: An evaluation of AI approaches to greenfield software engineering and programming

arXiv:2606.18293v2 Announce Type: replace-cross Abstract: Thanks to rapid developments in generative AI, we are in the midst of a paradigm shift that may change how we interact with computers forever.

2 Jul 2026

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VisReason: A Large-Scale Dataset for Visual Chain-of-Thought Reasoning

DGX agent

arXiv:2511.17731v2 Announce Type: replace Abstract: Chain-of-Thought (CoT) prompting has proven remarkably effective for eliciting complex reasoning in large language models (LLMs). Yet, its potential

model-releasesarxiv-cs-cv

2 Jul 2026

1/ On Training in Imagination - Dwarkesh's episode has a segment on dreaming as one of the next training paradigms. The idea is that a model…

1/ On Training in Imagination - Dwarkesh's episode has a segment on dreaming as one of the next training paradigms. The idea is that a model learns mostly inside its own, by imagining what would happe

researchyann-lecun--x

A Large-Language-Model Supported Personalized Driving Framework for Lane Change in Highway Scenarios

model-releasesarxiv-cs-ro

arXiv:2606.31483v1 Announce Type: new Abstract: Personalized driving can improve the user acceptance of automated driving systems. However, existing methods still provide limited support for translati

A Lifecycle and Application-Stack Survey of Large Language Model Vulnerabilities: Attacks, Risks, Defenses, and Open Problems

arXiv:2606.31639v1 Announce Type: cross Abstract: Large language models are no longer only text generators. They are increasingly embedded in retrieval pipelines, enterprise assistants, coding environ

A Realistic Protocol for Evaluation of Weakly Supervised Object Localization

arXiv:2404.10034v3 Announce Type: replace Abstract: Weakly Supervised Object Localization (WSOL) allows training deep learning models for classification and localization (LOC) using only global class-

A Stationary-Distribution Theory for Triplet-Based Plateau Search in Random Forest Ensemble-Size Selection

arXiv:2606.30837v1 Announce Type: cross Abstract: The number of trees is a central computational parameter in Random Forests: increasing it reduces finite-ensemble variability but increases training a

Absorption-Feature-Guided Distance-Decoupled Estimation and Band Selection for LWIR Hyperspectral Passive Ranging

arXiv:2606.31824v1 Announce Type: new Abstract: Long-wave infrared (LWIR) hyperspectral observations contain distance-dependent atmospheric absorption signatures, providing a physical basis for long-r

AC3S: Adaptive Conditioning for 3D-Aware Synthetic Data Generation

arXiv:2606.31204v1 Announce Type: new Abstract: Synthetic data generation has emerged as a powerful tool for improving data scalability in computer vision. Recent diffusion-based pipelines have demons

safetyarxiv-cs-cv

Accelerating Conformal Prediction via Approximate Leave-One-Out

arXiv:2606.31915v1 Announce Type: cross Abstract: While conformal prediction provides a general framework for uncertainty quantification in predictive inference, its application is often limited by co

researcharxiv-cs-lg

ADAPT: Attention Dynamics Alignment with Preference Tuning for Faithful MLLMs

arXiv:2606.31054v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) are critically hampered by hallucination, generating content inconsistent with the provided image. In this pa

Applications

Adapting Foundation ASR Models to Dysarthric Speech: A Case Study

arXiv:2606.31722v1 Announce Type: new Abstract: Automatic speech recognition (ASR) systems often perform poorly in dysarthric speech, limiting their usefulness to affected speakers in everyday communi

applicationsarxiv-cs-cl

Addressing Over-Refusal in LLMs with Competing Rewards

arXiv:2606.31748v1 Announce Type: new Abstract: Safety training on language models often induces over-refusal: improved safety on harmful prompts at the cost of increased refusal on harmless ones. Tho

safetyarxiv-cs-lg

Applications

AI-Generated PowerShell Malware: An Experimental Framework and Dataset

arXiv:2606.30819v1 Announce Type: cross Abstract: Generative AI has emerged as a significant cybersecurity threat, with several recent attack campaigns leveraging LLMs to generate code for malicious p

applicationsarxiv-cs-ai

AI Transparency: Governance Compliance or Stakeholder Requirements?

arXiv:2606.30652v1 Announce Type: cross Abstract: Transparency is increasingly mandated for public-sector AI systems, with organisations required to publish statements describing their AI use and over

AION: Aerial Indoor Object-Goal Navigation Using Dual-Policy Reinforcement Learning

model-releasesarxiv-cs-ro

arXiv:2601.15614v3 Announce Type: replace Abstract: Object-Goal Navigation (ObjectNav) requires an agent to autonomously explore an unknown environment and navigate toward target objects specified by

An AI-Based Solution for Secure Service Provisioning in IoT

arXiv:2606.30701v1 Announce Type: cross Abstract: As the Internet of Things (IoT) continues its rapid expansion, the attack surface grows accordingly, with emerging threats targeting smart objects and

An Executable Benchmarking Suite for Tool-Using Agents

arXiv:2605.11030v2 Announce Type: replace-cross Abstract: Closed-loop tool-using agents are increasingly evaluated in executable web, code, and micro-task environments, but benchmark reports often con

Attend, Transform, or Silence: Operator-Level Visual Skipping for Efficient Multimodal LLM Inference

arXiv:2606.31903v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) increasingly process long visual-token sequences, increasing the overall inference computation. Existing acce

Auditing Generalization in AI-Generated Video Detection: A Six-Control Protocol and the VidAudit Toolkit

arXiv:2606.31004v1 Announce Type: new Abstract: AI-generated video detection benchmarks such as GenVidBench and AIGVDBench are the de facto leaderboards, yet most evaluation protocols leave uncontroll

Automated Background Swapping for Robustness against Spurious Backgrounds

arXiv:2606.32018v1 Announce Type: new Abstract: Classifiers based on Deep Neural Networks exhibit strong performance across domains, yet can fail catastrophically if they rely on spurious correlations

Automating Cause-Effect Specification with Knowledge Graphs and Large Language Models

arXiv:2606.31614v1 Announce Type: cross Abstract: Engineering specifications such as interlocks, alarm rationalization tables, and cause-and-effect (C&E) matrices remain central to process control and

Beyond Binary Instrument QA: Probing Instrument Grounding in Music Audio-Language Models

arXiv:2606.31338v1 Announce Type: cross Abstract: Recent music audio-language models achieve high accuracy on instrument question-answering benchmarks, but it remains unclear whether this reflects rob

Beyond the Library: An Agentic Framework for Autoformalizing Research Mathematics

arXiv:2606.31134v1 Announce Type: new Abstract: While Large Language Models (LLMs) have demonstrated exceptional capabilities in mathematical reasoning, they frequently produce subtle errors that evad

BlockPilot: Instance-Adaptive Policy Learning for Diffusion-based Speculative Decoding

arXiv:2606.31315v1 Announce Type: new Abstract: Speculative decoding accelerates inference by using a lightweight draft model to generate candidate tokens in parallel, and are then verified by the tar

safetyarxiv-cs-cl

BP-TTA: Balanced and Prototype-Guided Test-Time Adaptation in Dynamic Scenarios

arXiv:2606.31420v1 Announce Type: new Abstract: Test-Time Adaptation (TTA) enables models trained on a source domain to adapt online to unlabeled test data under distribution shifts. While recent TTA

Bridging Video Understanding and Generation in a Unified Framework

arXiv:2606.31326v1 Announce Type: new Abstract: Recently, unified image generation and understanding have been extensively explored. However, extending such unified modeling paradigms to the video dom

Budget-Adaptive Routing: Skipping the Weak When the Strong Answers Anyway

arXiv:2606.30919v1 Announce Type: cross Abstract: Edge-cloud inference collaborations are often designed with a routing estimator that decides whether to offload each frame from weak models at the edg

Can VLMs Reason Robustly? A Neuro-Symbolic Investigation

arXiv:2603.23867v2 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) have been applied to a wide range of reasoning tasks, yet it remains unclear whether they can reason robustly un

Citation Discipline in Spec-Driven Development: A Cross-Model Empirical Study of Output Determinism and Automated Hallucination Detection in LLM-Generated Code

arXiv:2606.30689v1 Announce Type: cross Abstract: Spec-Driven Development (SDD) frameworks guide Large Language Model (LLM)-powered code generation through formal specifications, yet they differ funda

CoLT: Teaching Multi-Modal Models to Think with Chain of Latent Thoughts

arXiv:2606.31986v1 Announce Type: new Abstract: Chain-of-thought (CoT) reasoning has enabled multi-modal large language models (MLLMs) to tackle complex visual reasoning tasks by generating explicit i

Tutorials

CoMNet: A MedNeXt-CorrDiff Framework for Multi-Site Brain Tumor Segmentation

arXiv:2606.15305v2 Announce Type: replace Abstract: Accurate brain tumor segmentation from multiparametric magnetic resonance imaging (MRI) is critical for treatment planning, response assessment, and

tutorialsarxiv-cs-cv

Applications

Comparative Analysis of Machine Learning based Intrusion Detection in Realistic IoT Networks

arXiv:2606.31594v1 Announce Type: cross Abstract: The Internet of Things (IoT) is rapidly growing and expanding into various sectors, such as healthcare, transportation, smart homes, and more. Despite

applicationsarxiv-cs-ai

Continuous-Space Roadmap Generation for Mobile Robot Fleets with Distance Constraints and Geometry-Aware Discretization

arXiv:2511.07175v2 Announce Type: replace Abstract: Efficient routing of mobile robot fleets requires roadmaps with high redundancy, short path lengths, and sufficient node and edge clearance for conf

agentsarxiv-cs-ro

CooperScene: Multi-Modal Cooperative Autonomy Benchmark with C-V2X Communication Characterization

arXiv:2606.31219v1 Announce Type: new Abstract: Cellular vehicle-to-everything (C-V2X) enables cooperative perception, prediction, and planning beyond the field of view of individual agents. However,

Tutorials

Deductive Logic in Language Models: Horizontal vs Vertical Reasoning

arXiv:2510.09340v2 Announce Type: replace Abstract: Recent language models exhibit significant logical reasoning abilities, yet the mechanisms supporting deductive inference remain poorly understood.

tutorialsarxiv-cs-ai

Design and Implementation of Agentic Orchestrations and Orchestration of Agents

arXiv:2606.31518v1 Announce Type: new Abstract: Agentic Business Process Management has gained momentum recently. The prospect is that the autonomy of AI agents, i.e., predominantly LLM-based agents,

DPPE: Rethinking Camera-Based Positional Encoding for Scaling Multi-View Transformers

arXiv:2606.31585v1 Announce Type: cross Abstract: The remarkable scalability of Transformers has expanded their application to 3D computer vision, where camera-aware positional encoding is crucial for

DSIP: A Dynamic Coordination Planner for Signal-Free Intersections using Diffusion-Model-Based Multi-Agent Motion Planning

arXiv:2606.30694v1 Announce Type: cross Abstract: Traffic signal control at urban intersections inherently introduces stop-and-go behavior, resulting in increased delays and reduced traffic efficiency

Efficient Public Verification of Private ML via Regularization

model-releasesarxiv-cs-lg

arXiv:2512.04008v2 Announce Type: replace Abstract: Training with differential privacy (DP) guarantees dataset members that they cannot be identified by users of the released model. However, those dat

Efficient Sampling with Discrete Diffusion Models: Sharp and Adaptive Guarantees

arXiv:2602.15008v2 Announce Type: replace Abstract: Diffusion models over discrete spaces have recently shown striking empirical success, yet their theoretical foundations remain incomplete. In this p

researcharxiv-cs-lg

Energy-Optimal Spatial Iterative Learning within a Virtual Tube

model-releasesarxiv-cs-ro

arXiv:2606.31487v1 Announce Type: new Abstract: Due to the limited endurance of embedded energy sources such as lithium-polymer (LiPo) batteries, the flight duration and operational range of unmanned

Enhancing Graph Representations with Neighborhood-Contextualized Message-Passing

arXiv:2511.11046v3 Announce Type: replace-cross Abstract: Graph neural networks (GNNs) have become an indispensable tool for analyzing relational data. Classical GNNs are broadly classified into three

EpiMask: Leveraging Epipolar Distance Based Masks in Cross-Attention for Satellite Image Matching

arXiv:2603.21463v2 Announce Type: replace Abstract: The deep-learning based image matching networks can now handle significantly larger variations in viewpoints and illuminations while providing match

Estimating Supply Incrementality in Two-sided Marketplaces: A Causal Machine Learning Approach

arXiv:2606.30999v1 Announce Type: new Abstract: In two-sided marketplaces with heterogeneous products, it is important to understand the causal relationship between additional supply and marketplace o

researcharxiv-cs-lg

Estimating the Effect of Timing on Coupon Effectiveness

arXiv:2606.30664v1 Announce Type: cross Abstract: The coupon incentive is one of the most common tools marketers use to court users to engage with a business at various stages of the customer life cyc

FedXDS: Leveraging Model Attribution Methods to counteract Data Heterogeneity in Federated Learning

arXiv:2606.31742v1 Announce Type: cross Abstract: Explainable AI (XAI) methods have demonstrated significant success in recent years at identifying relevant features in input data that drive deep lear

Finite Difference Flow Optimization for RL Post-Training of Text-to-Image Models

arXiv:2603.12893v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) has become a standard technique for post-training diffusion-based image synthesis models, as it enables learning f