Search: “papers”

Analysis of Types of Inquiries in Student-AI Interaction: A case study of two CS2 tasks

arXiv:2608.17919v1 Announce Type: cross Abstract: Background and Context: Question and inquiry are integral parts of knowledge seeking and learning. Despite their importance, students tend not to ask

applicationsarxiv-cs-ai

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Research

ARASH: Adaptive Retrieval And Shot Selection for Tabular Prediction

DGX agent

arXiv:2608.17856v1 Announce Type: new Abstract: Tabular prediction is a critical task across numerous applications. The recent success of large language models has sparked various approaches for adapt

researcharxiv-cs-ai

19 Aug 2026

Backward through Time, Algebraically

arXiv:2608.17087v1 Announce Type: new Abstract: Linear temporal logic is a modal extension of propositional logic that allows one to state how a system should behave over time. Its canonical domain is

Benchmarking Classical and Transformer-Based Models for Document Sensitivity Classification

arXiv:2608.16928v1 Announce Type: new Abstract: Automatic sensitivity classification of organizational documents is a critical yet underserved problem, where the consequences of misclassification rang

Hardware

Beyond FLOPs: Energy-Aware Knowledge Distillation for Sustainable LLMs on Code-Related Task

arXiv:2608.17515v1 Announce Type: cross Abstract: Background: Large Language Models (LLMs) are increasingly being applied to Software Engineering (SE) tasks, achieving high accuracy across problems su

hardwarearxiv-cs-ai

Safety

Calibrated Predictive Safety for Heterogeneous Robots: An Action-Conditioned JEPA Framework with Model-Based Safety Shields

arXiv:2608.17496v1 Announce Type: new Abstract: Vision-language-action policies generalize broadly but provide no execution-time guarantees; classical model-based planners respect kinematic and geomet

safetyarxiv-cs-ro

Chain-of-Experience for Continual LLM Improvement

model-releasesarxiv-cs-cl

arXiv:2608.18027v1 Announce Type: new Abstract: Humans continuously learn from experience, whereas conventional large language model (LLM) evaluations ignore the models' ability to improve through inf

ChatPlanner: A Large Language Model Framework for Personalized Public Transit Routing

arXiv:2606.15315v2 Announce Type: replace Abstract: Personalized public transit routing in public transit systems remains challenging due to the difficulty of capturing and integrating diverse user pr

CoAL-RAG: A Complexity-Aware Legal Retrieval-Augmented Generation Method

arXiv:2608.17536v1 Announce Type: cross Abstract: Legal consultation questions exhibit multi-level complexity. A single retrieval strategy often leads to over-reasoning for simple questions and poor i

applicationsarxiv-cs-ai

Cognitive Graph Intelligence for Adaptive and Robust DDoS Attack Detection in Next Generation Networks

arXiv:2608.17352v1 Announce Type: new Abstract: Distributed Denial-of-Service (DDoS) attacks threaten network availability, requiring a cognitive detection process that senses traffic, infers intent,

Comparative Study of Out-of-the-Box Technology for Automatic Target Detection and Recognition

arXiv:2608.17917v1 Announce Type: cross Abstract: Automatic Target Detection and Recognition (ATD/R) is critical for military decision support and (semi-)autonomous operations. Recent advances in obje

Cross-Domain Generalization in Machine Unlearning via Label-Conditioned Energy Magnitude Regularization

model-releasesarxiv-cs-cv

arXiv:2608.17942v1 Announce Type: new Abstract: Machine unlearning removes the influence of specific data from a trained model. However, most methods treat the forgotten concept as isolated. In this p

DataSTORM: Deep Research on Large-Scale Databases using Exploratory Data Analysis and Data Storytelling

arXiv:2604.06474v2 Announce Type: replace Abstract: Deep research with Large Language Model (LLM) agents is emerging as a powerful paradigm for multi-step information discovery, synthesis, and analysi

agentsarxiv-cs-cl

Diffusion Models for Smarter UAVs: Decision-Making and Modeling

arXiv:2501.05819v2 Announce Type: replace-cross Abstract: Uncrewed Aerial Vehicles (UAVs) are increasingly used in modern communication networks. However, challenges in decision-making and digital mod

agentsarxiv-cs-ai

Do Large Language Models Play Six Degrees of Separation? Measuring Topological Compression in Long-Context Manifolds

arXiv:2608.17950v1 Announce Type: new Abstract: Large Language Models (LLMs) demonstrate remarkable multi-hop reasoning capabilities over long contexts, yet the internal mechanisms enabling these dist

researcharxiv-cs-cl

Evaluating the Diversity of AI-Generated Content with Diversity Profiles

arXiv:2608.17731v1 Announce Type: new Abstract: Diversity is a fundamental criterion for evaluating generative artificial intelligence (AI) systems, yet its measurement remains inherently ambiguous. E

Exact Reformulation and Optimization for Direct Metric Optimization in Binary Imbalanced Classification

arXiv:2507.15240v2 Announce Type: replace Abstract: For classification with imbalanced class frequencies, i.e., imbalanced classification (IC), standard accuracy is known to be misleading as a perform

From Global Benchmarks to Local Evaluations: Benchmarking LLMs for the German Public Sector

arXiv:2608.17827v1 Announce Type: new Abstract: Public institutions face a persistent challenge in selecting LLMs suited to their specific context. Existing benchmarks, however, are of limited use as

researcharxiv-cs-cl

From Student Risk Prediction to SC2R: Semantics-Constrained Counterfactual Recourse for Educational Decision Support

arXiv:2608.17618v1 Announce Type: cross Abstract: Learning analytics models can identify students at risk of poor performance, but they do not directly indicate which interventions are feasible, actio

applicationsarxiv-cs-ai

Future-Back Threat Modeling: A Foresight-Driven Security Framework

arXiv:2511.16088v3 Announce Type: replace-cross Abstract: Traditional threat modeling remains reactive-focused on known TTPs and past incident data, while threat prediction and forecasting frameworks

GADR: Gathering Architecture Decision Records from Meeting Transcriptions

arXiv:2608.17694v1 Announce Type: cross Abstract: Existing LLM-based approaches to Architecture Decision Record (ADR) generation share a critical and largely unexamined assumption: that input is alrea

agentsarxiv-cs-ai

General Semantic Knowledge Infusion for Spatio-Temporal Traffic Forecasting

arXiv:2608.17440v1 Announce Type: new Abstract: Although Graph Neural Networks (GNNs) have made significant advances in spatio-temporal traffic forecasting, their performance is limited when they rely

tutorialsarxiv-cs-lg

Global Convergence of Gradient EM for Over-Parameterized Gaussian Mixtures

arXiv:2506.06584v2 Announce Type: replace Abstract: Learning Gaussian Mixture Models (GMMs) is a fundamental problem in statistics and machine learning, with the Expectation-Maximization (EM) algorith

GSToken: Geometry-Structured Gaussian Tokens for Compact 3D Medical Image Representation

model-releasesarxiv-cs-cv

arXiv:2608.17425v1 Announce Type: new Abstract: Effective segmentation of multi-modal MRI is central to improving neural network accuracy in brain tumor recognition. Existing methods typically compres

Information fusion and machine learning for sensitivity analysis using physics knowledge and experimental data

arXiv:2608.17248v1 Announce Type: cross Abstract: When computational models (either physics-based or data-driven) are used for the sensitivity analysis of engineering systems, the sensitivity estimate

applicationsarxiv-cs-lg

Integrating Novelty and Surprise for Experience Prioritization and Exploration in Image-Based Reinforcement Learning

arXiv:2608.17373v1 Announce Type: cross Abstract: Sample efficiency is a central challenge in reinforcement learning (RL), particularly in image-based domains where agents must learn from high-dimensi

agentsarxiv-cs-ai

Intent-Driven Dynamic Chunking: Segmenting Documents to Reflect Predicted Information Needs

arXiv:2602.14784v1 Announce Type: cross Abstract: Breaking long documents into smaller segments is a fundamental challenge in information retrieval. Whether for search engines, question-answering syst

tutorialsarxiv-cs-ai

KernelArc: A Multi-Agent Framework for GPU Kernel Optimization

arXiv:2608.17071v1 Announce Type: new Abstract: We present KernelArc, a multi-agent framework for autonomous GPU kernel optimization across heterogeneous workloads. Strategy-specialized agents run in

Know3D: Prompting 3D Generation with Knowledge from Vision-Language Models

arXiv:2603.22782v2 Announce Type: replace Abstract: Recent advances in 3D generation have improved the fidelity and geometric details of synthesized 3D assets. However, due to the inherent ambiguity o

researcharxiv-cs-cv

Language Has Two Parameters: Narrative-Induced Semantic Plasticity and Phase-Sensitive Interpretation

model-releasesarxiv-cs-cl

arXiv:2608.18041v1 Announce Type: new Abstract: Language has two parameters. Count how often words occur together and you estimate amplitude, the strength of association. Word embeddings and attention

LLM Enhancement with Domain Expert Mental Model to Reduce LLM Hallucination with Causal Prompt Engineering

arXiv:2509.10818v2 Announce Type: replace Abstract: When consequential decisions depend on knowledge that exists nowhere in writing, LLMs hallucinate not from retrieval failure but from model absence.

LLM-Only PDDL Domain Repair with Open-Weight Models

arXiv:2608.17341v1 Announce Type: new Abstract: AI planning is concerned with finding a sequence of actions that achieves a specified goal. It relies on explicit models of the world, commonly represen

Looking Beyond the Scale: Do Surgical Skill Models Learn Transferable Representations Across Assessment Rubrics?

arXiv:2608.17519v1 Announce Type: new Abstract: Vision-based surgical skill assessment has shown strong in-domain results, yet a fundamental question remains unasked: do these models learn transferabl

tutorialsarxiv-cs-cv

LSem2Vec: A Simple yet Effective Two-Stage Approach for Source Code Embedding

arXiv:2409.14644v4 Announce Type: replace-cross Abstract: The advent of large language models (LLMs) has significantly advanced artificial intelligence in software engineering, with source code embedd

MagViT: Interpretable Multi-Magnification Transformers with Patient-Level Model Selection for Breast Histopathology

arXiv:2608.16959v1 Announce Type: cross Abstract: Breast cancer is one of the most common types of cancer among women around the world. Rapid detection and early treatment can hinder its progress to m

researcharxiv-cs-cv

Local Ai

Mixture-of-Expert Blocks Contain Strong Hallucination Detection Signals

arXiv:2608.17687v1 Announce Type: new Abstract: Despite their widespread use, Large Language Models (LLMs) remain limited by a fundamental problem: the generation of plausible but false content, known

local-aiarxiv-cs-ai

Multi-Observer Vehicle Localization Case Study with Roadside Radar and Connected Vehicle Sensing

arXiv:2608.16966v1 Announce Type: new Abstract: In modern intelligent transportation systems, it is essential to accurately estimate vehicle positions, especially in mixed traffic conditions where bot

applicationsarxiv-cs-cv

Hardware

Multi-Scale Spectral Attention Module-based Hyperspectral Segmentation in Autonomous Driving Scenarios

arXiv:2506.18682v3 Announce Type: replace-cross Abstract: Recent advances in autonomous driving (AD) have highlighted the potential of hyperspectral imaging (HSI) for enhanced environmental perception

hardwarearxiv-cs-ai

N-gram-like Language Models Predict Naturalistic Reading Time Best

arXiv:2603.09872v2 Announce Type: replace Abstract: Recent work has found that contemporary language models such as transformers can become so good at next-word prediction that the probabilities they

researcharxiv-cs-cl

NeuroAbs: A Neuro-Symbolic RTL Abstraction Framework for Property Checking Acceleration

arXiv:2608.17304v1 Announce Type: cross Abstract: Formal verification is a crucial technique for ensuring the functional correctness of hardware designs. In the context of property checking, a key cha

tutorialsarxiv-cs-ai

NGS-Marker: Robust Native Watermarking for 3D Gaussian Splatting

arXiv:2608.17447v1 Announce Type: new Abstract: With the rapid development and adoption of 3D Gaussian Splatting (3DGS), the need for effective copyright protection has become increasingly critical. E

applicationsarxiv-cs-cv

Nonlocal Transition Kernel for Efficient Learning of Restricted Boltzmann Machines

arXiv:2608.17450v1 Announce Type: cross Abstract: Learning restricted Boltzmann machines (RBMs) is computationally challenging because it requires expectations whose exact evaluation is generally intr

Online Generalized Sparse Regression: How Does Overparametrization Help?

arXiv:2608.17466v1 Announce Type: cross Abstract: Regularized sparse regression has been extensively studied in the offline setting, but online formulation remains relatively under-explored. This gap

Safety

Proactive Road Safety Intervention in Australia: Predicting Risky Driving Hotspots from Connected Vehicle Data

arXiv:2608.16913v1 Announce Type: new Abstract: Road safety monitoring has historically been reactive, relying on crash-record analysis after fatalities and injuries have already occurred. Proactive i

safetyarxiv-cs-lg

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

model-releasesarxiv-cs-cl

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

Safety

Reinforcement Learning as (Discrete) Potential Theory

arXiv:2608.17181v1 Announce Type: new Abstract: Reinforcement learning (RL) theory fundamentally depends on probability theory through the Markov chain. There is a deep connection between probability

safetyarxiv-cs-lg

Revisiting WEASEL 2.0: Reproduction, Sensitivity, and an Adaptive Ensemble-Size Rule

arXiv:2608.18021v1 Announce Type: new Abstract: WEASEL 2.0 is a dictionary-based time series classifier that combines dilated sliding windows with a randomised hyperparameter ensemble and a fixed-size

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