Search: “models”

Pedestrians play chicken with an autonomous vehicle

arXiv:2604.24384v1 Announce Type: new Abstract: Automated vehicles (AVs) are commonly programmed to yield unconditionally to pedestrians in the interest of safety. However, this design choice can give

safetyarxiv-cs-ro

Personalized Worked Example Generation from Student Code Submissions using Pattern-based Knowledge Components

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

DGX agent

arXiv:2604.24758v1 Announce Type: cross Abstract: Adaptive programming practice often relies on fixed libraries of worked examples and practice problems, which require substantial authoring effort and

researcharxiv-cs-ai

28 Apr 2026

PExA: Parallel Exploration Agent for Complex Text-to-SQL

arXiv:2604.22934v1 Announce Type: new Abstract: LLM-based agents for text-to-SQL often struggle with latency-performance trade-off, where performance improvements come at the cost of latency or vice v

Agents

PhySE: A Psychological Framework for Real-Time AR-LLM Social Engineering Attacks

arXiv:2604.23148v1 Announce Type: new Abstract: The emerging threat of AR-LLM-based Social Engineering (AR-LLM-SE) attacks (e.g. SEAR) poses a significant risk to real-world social interactions. In su

agentsarxiv-cs-ai

Physics-Informed Temporal U-Net for High-Fidelity Fluid Interpolation

arXiv:2604.23372v1 Announce Type: cross Abstract: Reconstructing high-fidelity fluid dynamics from sparse temporal observations is quite challenging, mainly due to the chaotic and non-linear nature of

researcharxiv-cs-cv

POPI: Personalizing LLMs via Optimized Natural Language Preference Inference

arXiv:2510.17881v3 Announce Type: replace-cross Abstract: Large language models (LLMs) are typically aligned with population-level preferences, despite substantial variation across individual users. W

PRAXIS: Integrating Program Analysis with Observability for Root-Cause Analysis

arXiv:2512.22113v2 Announce Type: replace-cross Abstract: Unresolved production cloud incidents cost an average of over $2M per hour. This paper introduces PRAXIS, an orchestrator that manages and dep

Question-Adaptive Graph Learning for Multi-hop Retrieval Augmented Generation

arXiv:2510.11541v2 Announce Type: replace-cross Abstract: Retrieval-augmented generation (RAG) has demonstrated its ability to enhance Large Language Models (LLMs) by integrating external knowledge so

Rank, Head-Channel Non-Identifiability, and Symmetry Breaking: A Precise Analysis of Representational Collapse in Transformers

model-releasesarxiv-cs-cl

arXiv:2604.23681v1 Announce Type: cross Abstract: A widely cited result by Dong et al. (2021) showed that Transformers built from self-attention alone, without skip connections or feed-forward layers,

RAT: RunAnyThing via Fully Automated Environment Configuration

arXiv:2604.23190v1 Announce Type: cross Abstract: Automating repository-level software engineering tasks is a foundational challenge for autonomous code agents, largely due to the difficulty of config

Real-time windrow detection from onboard tractor sensors for automated following

model-releasesarxiv-cs-ro

arXiv:2604.24628v1 Announce Type: new Abstract: Proprietary design in commercial windrow-detection systems restricts transparency and limits progress in open autonomous forage-harvesting research. We

Reasonably reasoning AI agents can avoid game-theoretic failures in zero-shot, provably

arXiv:2603.18563v2 Announce Type: replace Abstract: As autonomous AI agents increasingly mediate online platform markets, a fundamental question emerges: do these markets generate stable strategic out

Applications

RedParrot: Accelerating NL-to-DSL for Business Analytics via Query Semantic Caching

arXiv:2604.22758v1 Announce Type: cross Abstract: Recently, at Xiaohongshu, the rapid expansion of e-commerce and advertising demands real-time business analytics with high accuracy and low latency. T

applicationsarxiv-cs-ai

Reheat Nachos for Dinner? Evaluating AI Support for Cross-Cultural Communication of Neologisms

arXiv:2604.23842v1 Announce Type: cross Abstract: Neologisms and emerging slang are central to daily conversation, yet challenging for non-native speakers (NNS) to interpret and use appropriately in c

Local Ai

Reliable Microservice Tail Latency Prediction via Decoupled Dual-Stream Learning and Gradient Modulation

arXiv:2508.01635v2 Announce Type: replace-cross Abstract: Microservice architectures enable scalable cloud-native applications; however, the distributed nature of these systems complicates the mainten

local-aiarxiv-cs-ai

Hardware

RetroInfer: A Vector Storage Engine for Scalable Long-Context LLM Inference

arXiv:2505.02922v3 Announce Type: replace Abstract: Recent large language models (LLMs) are rapidly extending their context windows, yet inference throughput lags due to increasing GPU memory and band

hardwarearxiv-cs-lg

Robust and Clinically Reliable EEG Biomarkers: A Cross Population Framework for Generalizable Parkinson's Disease Detection

arXiv:2604.23933v1 Announce Type: new Abstract: Developing robust and clinically reliable EEG biomarkers requires evaluation frameworks that explicitly address cross population generalization in multi

researcharxiv-cs-lg

Robust Audio-Text Retrieval via Cross-Modal Attention and Hybrid Loss

model-releasesarxiv-cs-cl

arXiv:2604.23323v1 Announce Type: new Abstract: Audio-text retrieval enables semantic alignment between audio content and natural language queries, supporting applications in multimedia search, access

Robust Least-Squares Optimization for Data-Driven Predictive Control: A Geometric Approach

arXiv:2511.09242v2 Announce Type: replace-cross Abstract: The paper studies a geometrically robust least-squares problem that extends classical and norm-based robust formulations. Rather than minimizi

researcharxiv-cs-lg

Agents

SeaEvo: Advancing Algorithm Discovery with Strategy Space Evolution

arXiv:2604.24372v1 Announce Type: cross Abstract: LLM-guided evolutionary search has emerged as a promising paradigm for automated algorithm discovery, yet most systems track search progress primarily

agentsarxiv-cs-ai

Self-Admitted Technical Debt Detection Approaches: A Decade Systematic Review

arXiv:2312.15020v4 Announce Type: replace-cross Abstract: Technical debt (TD) refers to the long-term costs associated with suboptimal design or code decisions in software development, often made to m

SFT-then-RL Outperforms Mixed-Policy Methods for LLM Reasoning

arXiv:2604.23747v1 Announce Type: cross Abstract: Recent mixed-policy optimization methods for LLM reasoning that interleave or blend supervised and reinforcement learning signals report improvements

ShapeUP: Scalable Image-Conditioned 3D Editing

arXiv:2602.05676v2 Announce Type: replace Abstract: Recent advancements in 3D foundation models have enabled the generation of high-fidelity assets, yet precise 3D manipulation remains a significant c

researcharxiv-cs-cv

SoccerRef-Agents: Multi-Agent System for Automated Soccer Refereeing

arXiv:2604.23392v1 Announce Type: new Abstract: Refereeing is vital in sports, where fair, accurate, and explainable decisions are fundamental. While intelligent assistant technologies are being widel

SolarFCD: A Large-Scale Dataset and Benchmark for Solar Fault Classification in Photovoltaic Systems

model-releasesarxiv-cs-cv

arXiv:2604.23662v1 Announce Type: new Abstract: The increasing global deployment of solar photovoltaic (PV) systems needs robust, scalable, and automated inspection technologies capable of detecting a

SpecRLBench: A Benchmark for Generalization in Specification-Guided Reinforcement Learning

model-releasesarxiv-cs-lg

arXiv:2604.24729v1 Announce Type: new Abstract: Specification-guided reinforcement learning (RL) provides a principled framework for encoding complex, temporally extended tasks using formal specificat

Spectro-Temporal Modulation Representation Framework for Human-Imitated Speech Detection

arXiv:2604.23241v1 Announce Type: cross Abstract: Human-imitated speech poses a greater challenge than AI-generated speech for both human listeners and automatic detection systems. Unlike AI-generated

researcharxiv-cs-cl

Local Ai

Statistical Test for Diffusion-Based Anomaly Localization via Selective Inference

arXiv:2402.11789v5 Announce Type: replace-cross Abstract: Anomaly localization in images -- identifying regions that deviate from normal patterns -- is vital in applications such as medical diagnosis

local-aiarxiv-cs-cv

STELLAR-E: a Synthetic, Tailored, End-to-end LLM Application Rigorous Evaluator

arXiv:2604.24544v1 Announce Type: new Abstract: The increasing reliance on Large Language Models (LLMs) across diverse sectors highlights the need for robust domain-specific and language-specific eval

StereoSpace: Depth-Free Synthesis of Stereo Geometry via End-to-End Diffusion in a Canonical Space

arXiv:2512.10959v2 Announce Type: replace Abstract: We introduce StereoSpace, a diffusion-based framework for monocular-to-stereo synthesis that models geometry purely through viewpoint conditioning,

tutorialsarxiv-cs-cv

StratRAG: A Multi-Hop Retrieval Evaluation Dataset for Retrieval-Augmented Generation Systems

arXiv:2604.22757v1 Announce Type: cross Abstract: We introduce StratRAG, an open-source retrieval evaluation dataset for benchmarking Retrieval-Augmented Generation (RAG) systems on multi-hop reasonin

Structure Guided Retrieval-Augmented Generation for Factual Queries

arXiv:2604.22843v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) has been proposed to mitigate hallucinations in large language models (LLMs), where generated outputs may be fact

Supernodes and Halos: Loss-Critical Hubs in LLM Feed-Forward Layers

model-releasesarxiv-cs-cl

arXiv:2604.23475v1 Announce Type: cross Abstract: We study the organization of channel-level importance in transformer feed-forward networks (FFNs). Using a Fisher-style loss proxy (LP) based on activ

Survey in Characterizing Semantic Change

arXiv:2402.19088v5 Announce Type: replace-cross Abstract: Live languages continuously evolve to integrate the cultural change of human societies. This evolution manifests through neologisms (new words

TCOD: Exploring Temporal Curriculum in On-Policy Distillation for Multi-turn Autonomous Agents

arXiv:2604.24005v1 Announce Type: cross Abstract: On-policy distillation (OPD) has shown strong potential for transferring reasoning ability from frontier or domain-specific models to smaller students

The Alignment Target Problem: Divergent Moral Judgments of Humans, AI Systems, and Their Designers

arXiv:2604.24155v1 Announce Type: cross Abstract: The quest to align machine behavior with human values raises fundamental questions about the moral frameworks that should govern AI decision-making. M

The Optimal Sample Complexity of Multiclass and List Learning

model-releasesarxiv-cs-lg

arXiv:2604.24749v1 Announce Type: new Abstract: While the optimal sample complexity of binary classification in terms of the VC dimension is well-established, determining the optimal sample complexity

TopoHR: Hierarchical Centerline Representation for Cyclic Topology Reasoning in Driving Scenes with Point-to-Instance Relations

model-releasesarxiv-cs-cv

arXiv:2604.24119v1 Announce Type: new Abstract: Topology reasoning is crucial for autonomous driving. Current methods primarily focus on instance-level learning for centerline detection, followed by a

TSAssistant: A Human-in-the-Loop Agentic Framework for Automated Target Safety Assessment

arXiv:2604.23938v1 Announce Type: new Abstract: Target Safety Assessment (TSA) requires systematic integration of heterogeneous evidence, including genetic, transcriptomic, target homology, pharmacolo

safetyarxiv-cs-cl

Unveiling the Backdoor Mechanism Hidden Behind Catastrophic Overfitting in Fast Adversarial Training

arXiv:2604.24350v1 Announce Type: cross Abstract: Fast Adversarial Training (FAT) has attracted significant attention due to its efficiency in enhancing neural network robustness against adversarial a

Utility-Aware Data Pricing: Token-Level Quality and Empirical Training Gain for LLMs

arXiv:2604.22893v1 Announce Type: cross Abstract: Traditional data valuation methods based on ``row-count imes quality coefficient'' paradigms fail to capture the nuanced, nonlinear contributions that

What Prompts Don't Say: Understanding and Managing Underspecification in LLM Prompts

arXiv:2505.13360v3 Announce Type: replace Abstract: Prompt underspecification is a common challenge when interacting with LLMs. In this paper, we present an in-depth analysis of this problem, showing

researcharxiv-cs-cl

When Context Sticks: Studying Interference in In-Context Learning

arXiv:2604.23371v1 Announce Type: new Abstract: This paper investigates context stickiness in in-context learning (ICL), a phenomenon where earlier examples in a prompt interfere with a transformer's

researcharxiv-cs-lg

When Policies Cannot Be Retrained: A Unified Closed-Form View of Post-Training Steering in Offline Reinforcement Learning

arXiv:2604.22873v1 Announce Type: cross Abstract: Offline reinforcement learning (RL) can learn effective policies from fixed datasets, but deployment objectives may change after training, and in many

Agents

WinkTPG: An Execution Framework for Multi-Agent Path Finding Using Temporal Reasoning

arXiv:2508.01495v2 Announce Type: replace Abstract: Planning collision-free paths for a large group of agents is a challenging problem in many real-world applications. While recent advances in Multi-A

agentsarxiv-cs-ai

XGRAG: A Graph-Native Framework for Explaining KG-based Retrieval-Augmented Generation

arXiv:2604.24623v1 Announce Type: new Abstract: Graph-based Retrieval-Augmented Generation (GraphRAG) extends traditional RAG by using knowledge graphs (KGs) to give large language models (LLMs) a str

XITE: Cross-lingual Interpolation for Transfer using Embeddings

arXiv:2604.23589v1 Announce Type: new Abstract: Facilitating cross-lingual transfer in multilingual language models remains a critical challenge. Towards this goal, we propose an embedding-based data

researcharxiv-cs-cl

Applications

Your Reviews Replicate You: LLM-Based Agents as Customer Digital Twins for Conjoint Analysis

arXiv:2604.22756v1 Announce Type: cross Abstract: Conjoint analysis is a cornerstone of market research for estimating consumer preferences; however, traditional methods face persistent challenges reg

applicationsarxiv-cs-ai