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ProSPy: A Profiling-Driven SQL-Python Agentic Framework for Enterprise Text-to-SQL

arXiv:2606.05836v1 Announce Type: new Abstract: Large language models have substantially advanced Text-to-SQL systems, yet applying them to enterprise-scale databases remains challenging. Real-world d

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QueryAgent-R1: Bridging Query Generation and Product Retrieval for E-Commerce Query Recommendation

DGX agent

arXiv:2606.05671v1 Announce Type: new Abstract: Query recommendation in e-commerce search aims to proactively suggest queries that match users' potential interests. However, existing methods mainly op

safetyarxiv-cs-cl

5 Jun 2026

Local Ai

RadiusFPS: Efficient Farthest Point Sampling on CPUs and GPUs via Spherical Voxel Pruning

arXiv:2606.06255v1 Announce Type: cross Abstract: Point clouds are a primary sensory representation for robotic perception, underpinning LiDAR-based autonomous driving, simultaneous localization and m

local-aiarxiv-cs-cv

RAPTOR+: A Visually Grounded Vision-Language Framework to Improve Clinical Trust and Auditability in Automated Cancer Referral Processing

model-releasesarxiv-cs-cv

arXiv:2605.25956v2 Announce Type: replace Abstract: Urgent suspected colorectal cancer (CRC) referrals create operational bottlenecks because semi-structured clinical documents often require manual re

Real-Time Threat Detection from Surveillance Cameras using Machine Learning

arXiv:2606.05708v1 Announce Type: new Abstract: Ensuring public safety in densely populated urban environments remains a critical challenge, necessitating the deployment of intelligent and automated v

RealDexUMI: A Wearable Universal Manipulation Interface for Dexterous Robot Learning

arXiv:2606.06033v1 Announce Type: new Abstract: Learning dexterous manipulation requires demonstrations that preserve fine hand-object interactions while remaining executable at deployment. Existing p

researcharxiv-cs-ro

ReasoningFlow: Discourse Structures for Understanding LLM Reasoning Traces

arXiv:2606.05402v1 Announce Type: new Abstract: Large reasoning models (LRMs) produce reasoning traces with non-linear structures, such as backtracking and self-correction, that complicate the evaluat

ReCache: Learning Budget-Aware Caching Schedules for Diffusion Models via REINFORCE

arXiv:2606.06060v1 Announce Type: new Abstract: Modern diffusion models generate high-quality images and videos, but their iterative denoising process makes inference expensive. Feature caching accele

Recovering Physically Plausible Human-Object Interactions from Monocular Videos

arXiv:2606.05359v1 Announce Type: new Abstract: In this paper, we propose RePHO, a method to reconstruct physically plausible human-object interactions (HOI) from monocular videos. While existing kine

RedditPersona: A Modular Framework for Community-Conditioned LLM Adaptation from Reddit

arXiv:2606.06027v1 Announce Type: cross Abstract: Community-conditioned language model adaptation requires choices about data collection, community definition, and evaluation that are currently made i

Reducing Hallucinations in Complex Question Answering using Simple Graph-based Retrieval-Augmented Generation (long version)

arXiv:2606.05901v1 Announce Type: new Abstract: Large language models (LLMs) have fundamentally transformed the landscape of Natural Language Processing. Despite these advances, LLMs and LLM-based sys

Reinforcement Learning Elicits Contextual Learning of Unseen Language Translation

arXiv:2606.06428v1 Announce Type: new Abstract: Prior work has shown that large language models (LLMs) can translate unseen or low-resource languages by undergoing continued training or even by encodi

Representing Research Attention as Contextually Structured Flows

arXiv:2606.05895v1 Announce Type: new Abstract: Research attention is widely used as an indicator of visibility, influence, and societal uptake, yet it is typically represented as aggregated counts th

ReSAGE-PAR: Representational Similarity Assessment for Generative Expansion in Pedestrian Attribute Recognition

arXiv:2606.06020v1 Announce Type: new Abstract: To address the limited diversity and data scarcity in Pedestrian Attribute Recognition (PAR), we explore image synthesis using diffusion models guided b

Resonant Minds: Closed-Loop Social Avatars with Theory of Mind

arXiv:2606.05896v1 Announce Type: new Abstract: Creating lifelike digital humans with genuine social intelligence requires unifying cognitive reasoning and multimodal generation within a coherent fram

agentsarxiv-cs-cv

Rethinking LoRA Memory Through the Lens of KV Cache Compression

arXiv:2606.05698v1 Announce Type: new Abstract: Parametric retrieval augmentation encodes document information into lightweight, document-specific modules such as LoRA adapters, reducing the need to i

ReTreVal: Reasoning Tree with Validation and Cross-Problem Memory for Large Language Models

arXiv:2601.02880v2 Announce Type: replace-cross Abstract: Every existing inference-time reasoning framework discards all failure context at problem boundaries, leaving a model solving problem 500 no w

Retrospective Harness Optimization: Improving LLM Agents via Self-Preference over Trajectory Rollouts

arXiv:2606.05922v1 Announce Type: cross Abstract: AI agents rely on a harness of skills, tools, and workflows to solve complex problems. Continually improving this harness is essential for adapting to

agentsarxiv-cs-cl

ReverseEOL: Improving Training-free Text Embeddings via Text Reversal in Decoder-only LLMs

arXiv:2606.05858v1 Announce Type: new Abstract: Recent advances in Large Language Models (LLMs) have opened new avenues for generating training-free text embeddings. However, the causal attention in d

Revising Context, Shifting Simulated Stance: Auditing LLM-Based Stance Simulation in Online Discussions

arXiv:2606.06443v1 Announce Type: new Abstract: Large language models are increasingly used to simulate social media users and infer how individuals may respond to online discussions. However, it rema

Revisiting Lexicon Evaluation in Unsupervised Word Discovery

arXiv:2606.06183v1 Announce Type: cross Abstract: Building a lexicon from discovered word-like units is a central goal in zero-resource speech processing. But do our evaluations provide a trustworthy

safetyarxiv-cs-cl

RhymeFlow: Training-Free Acceleration for Video Generation with Asynchronous Denoising Flow Scheduling

arXiv:2606.06309v1 Announce Type: new Abstract: Video generation models based on Diffusion Transformers (DiTs) have achieved remarkable performance in video synthesis, yet they suffer from high infere

tutorialsarxiv-cs-cv

RiskFlow: Fast and Faithful Safety-Critical Traffic Scenario Generation

arXiv:2606.06423v1 Announce Type: new Abstract: Safety-critical traffic scenario generation is essential for evaluating autonomous driving systems under rare but high-risk interactions. Existing diffu

safetyarxiv-cs-ro

Robust Scene Transfer for PointGoal Navigation via Privileged Sensor Guided Contrastive Learning

arXiv:2606.05506v1 Announce Type: new Abstract: We propose a sensor-guided adaptive contrastive learning framework for visual representation learning in PointGoal navigation. During training, privileg

RoCA: Robust Cross-Domain End-to-End Autonomous Driving

arXiv:2506.10145v3 Announce Type: replace Abstract: End-to-end (E2E) autonomous driving has recently emerged as a new paradigm, offering significant potential. However, few studies have looked into th

agentsarxiv-cs-cv

RQUL-UIE: Revitalizing Quality-Unstable Labels for Underwater Image Enhancement via In-Dataset Self-Supervision

arXiv:2606.06176v1 Announce Type: new Abstract: Underwater Image Enhancement (UIE) is essential for mitigating degradations caused by water medium. Although learning-based methods have advanced signif

Safe Embodied AI for Long-horizon Tasks: A Cross-layer Analysis of Robotic Manipulation

model-releasesarxiv-cs-ro

arXiv:2606.05660v1 Announce Type: new Abstract: Embodied AI systems are increasingly expected to reason and act over extended horizons in physical environments. This growing capability brings safety t

SAM-Flow: Source-Anchored Masked Flow for Training-Free Image Editing

arXiv:2606.06228v1 Announce Type: new Abstract: Training-free image editing has recently attracted increasing attention due to its ability to modify real images using powerful pre-trained diffusion an

Sample-efficient Low-level Motion Planning for Robotic Manipulation Tasks via Zero-shot Transfer Learning

arXiv:2606.06041v1 Announce Type: new Abstract: As robotic systems become more sophisticated, the growing complexity of their motion planning models and the longer training times pose substantial chal

tutorialsarxiv-cs-ro

SC-MFJ: A Simple Haptic Quality Metric for Medical Image Segmentation

arXiv:2606.06199v1 Announce Type: new Abstract: Standard segmentation metrics such as Dice and Hausdorff distance measure geometric overlap but say nothing about whether a segmented surface is suitabl

Scaffold, Not Vocabulary? A Controlled, Two-Tier, Pre-Registered Study of a Popperian Code-Generation Skill

arXiv:2606.06454v1 Announce Type: cross Abstract: Large language models increasingly write, review, and judge code, and a fast-growing practice equips them with prompt 'skills' that ask the model to r

Second-order Gaussian directional derivative representations for image high-resolution corner detection

arXiv:2601.08182v2 Announce Type: replace Abstract: Corner detection is widely used in various computer vision tasks, such as image matching and 3D reconstruction. Our research indicates that there ar

tutorialsarxiv-cs-cv

Seeing is Believing? Evaluating Vision-Language Model Susceptibility in Agent-to-Agent Multimodal Persuasion

arXiv:2510.22768v2 Announce Type: replace Abstract: As autonomous agents increasingly interact, they inevitably attempt to influence one another. While prior work in text-only settings has explored th

Seeing Time: Benchmarking Chronological Reasoning and Shortcut Biases in Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2606.05702v1 Announce Type: cross Abstract: Recent advancements in Vision-Language Models (VLMs) have significantly enhanced their ability to interpret complex visual semantics, yet their capaci

Self-Augmenting Retrieval for Diffusion Language Models

arXiv:2606.06474v1 Announce Type: new Abstract: Discrete diffusion language models generate text by iteratively denoising an entire response in parallel. At each step, they predict tentative tokens fo

tutorialsarxiv-cs-cl

Self-Learning Expression Deformations for Data-Efficient Gaussian Avatars

arXiv:2606.05912v1 Announce Type: new Abstract: Modeling dynamic facial expressions using 3D Gaussian representations remains challenging due to their unstructured nature. Conventional Gaussian avatar

Self-supervised Feature Disentanglement and Augmentation Network for One-class Face Anti-spoofing

arXiv:2503.22929v3 Announce Type: replace Abstract: Face anti-spoofing (FAS) techniques aim to enhance the security of facial identity authentication by distinguishing authentic live faces from decept

Self-supervised User Profile Generation for Personalization

arXiv:2606.05336v1 Announce Type: new Abstract: Personalizing large language models (LLMs) has become a central challenge as LLMs are deployed across recommendation, search, dialogue, and content gene

Hardware

Semantic-decoupled Spatial Partition Guided Point-supervised Oriented Object Detection

arXiv:2506.10601v2 Announce Type: replace Abstract: Given its ability to reduce annotation costs, weakly supervised learning based on single-point annotations has emerged as a research focus in orient

hardwarearxiv-cs-cv

Semi-Offline Reinforcement Learning for Optimized Text Generation

arXiv:2306.09712v2 Announce Type: replace-cross Abstract: In reinforcement learning (RL), there are two major settings for interacting with the environment: online and offline. Online methods explore

ShotCrop^3: Cropping Human-Centric Images into Cinematic Triple-Shot Compositions

model-releasesarxiv-cs-cv

arXiv:2606.05635v1 Announce Type: new Abstract: Prior work on aesthetic composition typically produces a single aesthetically pleasing crop, overlooking the narrative value of composing multiple shots

SkillComposer: Learning to Evolve Agent Skills for Specification and Generalization

arXiv:2606.06079v1 Announce Type: new Abstract: Agent skills, which consist of reusable strategies that guide agent reasoning and action, have shown strong potential for improving model capability at

agentsarxiv-cs-cl

SoCRATES: Towards Reliable Automated Evaluation of Proactive LLM Mediation across Domains and Socio-cognitive Variations

arXiv:2606.05563v1 Announce Type: cross Abstract: Evaluating LLM mediators remains challenging, as mediation unfolds as a real-time trajectory shaped by disputants' shifting emotions, intentions, and

SpanNorm: Reconciling Training Stability and Performance in Deep Transformers

arXiv:2601.22580v2 Announce Type: replace Abstract: The success of Large Language Models (LLMs) hinges on the stable training of deep Transformer architectures. A critical design choice is the placeme

Stability vs. Manipulability: Evaluating Robustness Under Post-Decision Interaction in LLM Judges

arXiv:2606.05384v1 Announce Type: cross Abstract: LLM-as-judge evaluation is widely used in benchmarking pipelines, where model outputs are compared and ranked using automated evaluators. These pipeli

Hardware

Staged Factorial Screening for Budget-Constrained Micro-Pretraining

arXiv:2606.05186v1 Announce Type: cross Abstract: Budget-constrained micro-pretraining often requires triaging many candidate recipes on a shared accelerator before larger search budgets are spent. We

hardwarearxiv-cs-cl

Local Ai

Statistical Priors for Implicit Preferences: Decoupling Skill Selection as a Local Harness in Personal Agents

arXiv:2606.05828v1 Announce Type: cross Abstract: As Large Language Model (LLM) capabilities advance, locally deployed personal agents relying on API-based remote models and external skills have emerg

local-aiarxiv-cs-cl

Statistically Reliable LLM-Based Ranking Evaluation via Prediction-Powered Inference

arXiv:2606.05308v1 Announce Type: cross Abstract: With PRECISE, we extended Prediction-Powered Inference to produce bias-corrected estimates of ranking evaluation metrics by combining a small human-la