All entries

Skew-adaptive conformal prediction

arXiv:2605.16145v1 Announce Type: cross Abstract: We develop a skew-adaptive extension of split conformal prediction for regression. The method starts from an asymmetric interval family centered at a

tutorialsarxiv-cs-lg

SKILL0: In-Context Agentic Reinforcement Learning for Skill Internalization

Source

Human DGX agent

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

arXiv:2604.02268v2 Announce Type: replace Abstract: Agent skills, structured packages of procedural knowledge and executable resources that agents dynamically load at inference time, have become a rel

safetyarxiv-cs-lg

18 May 2026

SkillSmith: Compiling Agent Skills into Boundary-Guided Runtime Interfaces

arXiv:2605.15215v1 Announce Type: new Abstract: Recently, skills have been widely adopted in large language model (LLM)-based agent systems across various domains. In existing frameworks, skills are t

SkiP: When to Skip and When to Refine for Efficient Robot Manipulation

arXiv:2605.15536v1 Announce Type: cross Abstract: Previous imitation learning policies predict future actions at every control step, whether in smooth motion phases or precise, contact-rich operation

safetyarxiv-cs-ai

SkyLink: A Large Vision-Language Model Driven Re-ranking Framework for Cross-View UAV geolocalization

arXiv:2603.08063v3 Announce Type: replace Abstract: Cross-view UAV geolocalization is fundamentally a challenging large-scale image retrieval task, aiming to determine the geographic coordinates of Un

Skyra: AI-Generated Video Detection via Grounded Artifact Reasoning

arXiv:2512.15693v2 Announce Type: replace Abstract: The misuse of AI-driven video generation technologies has raised serious social concerns, highlighting the urgent need for reliable AI-generated vid

SLIP & ETHICS: Graduated Intervention for AI Emotional Companions

arXiv:2605.15915v1 Announce Type: cross Abstract: AI emotional companions face a safety-rapport paradox: restrictive safeguards can damage supportive alliance, while permissive systems risk user harm.

safetyarxiv-cs-ai

Small Generalizable Prompt Predictive Models Can Steer Efficient RL Post-Training of Large Reasoning Models

arXiv:2602.01970v2 Announce Type: replace Abstract: Reinforcement learning enhances the reasoning capabilities of large language models but often involves high computational costs due to rollout-inten

SMCEvolve: Principled Scientific Discovery via Sequential Monte Carlo Evolution

arXiv:2605.15308v1 Announce Type: new Abstract: LLM-driven program evolution has emerged as a powerful tool for automated scientific discovery, yet existing frameworks offer no principled guide for de

tutorialsarxiv-cs-ai

SMMBench: A Benchmark for Source-Distributed Multimodal Agent Memory

model-releasesarxiv-cs-cl

arXiv:2605.15710v1 Announce Type: new Abstract: Existing benchmarks for multimodal memory reasoning largely evaluate systems within pre-assembled contexts, but under-evaluate whether agents can use ev

Smoothie: Smoothing Diffusion on Token Embeddings for Text Generation

arXiv:2505.18853v2 Announce Type: replace Abstract: Diffusion models have achieved state-of-the-art performance in generating images, audio, and video, but their adaptation to text remains challenging

researcharxiv-cs-cl

Social-Mamba: Socially-Aware Trajectory Forecasting with State-Space Models

arXiv:2605.15424v1 Announce Type: new Abstract: Human trajectory forecasting is crucial for safe navigation in crowded environments, requiring models that balance accuracy with computational efficienc

SOLAR: Self-supervised Joint Learning for Symmetric Multimodal Retrieval

arXiv:2605.15868v1 Announce Type: new Abstract: In this work, we address the critical yet underexplored challenge of symmetric multimodal-to-multimodal (MM2MM) retrieval, where queries and contexts ar

Agents

Solvita: Enhancing Large Language Models for Competitive Programming via Agentic Evolution

arXiv:2605.15301v1 Announce Type: new Abstract: Large language models (LLMs) still struggle with the rigorous reasoning demands of hard competitive programming. While recent multi-agent frameworks att

agentsarxiv-cs-ai

Local Ai

Sound Sparks Motion: Audio and Text Tuning for Video Editing

arXiv:2605.15307v1 Announce Type: cross Abstract: Motion-centric video editing remains difficult for large generative video models, which often respond well to appearance changes but struggle to produ

local-aiarxiv-cs-cv

Sparse ActionGen: Accelerating Diffusion Policy with Real-time Pruning

arXiv:2601.12894v2 Announce Type: replace-cross Abstract: Diffusion Policy has dominated action generation due to its strong capabilities for modeling multi-modal action distributions, but its multi-s

Sparse Autoencoders enable Robust and Interpretable Fine-tuning of CLIP models

arXiv:2605.15961v1 Announce Type: new Abstract: Large-scale pre-trained vision-language models like CLIP demonstrate remarkable zero-shot performance across diverse tasks. However, fine-tuning these m

researcharxiv-cs-cv

Spectral Priors vs. Attention: Investigating the Utility of Attention Mechanisms in EEG-Based Diagnosis

arXiv:2605.15433v1 Announce Type: new Abstract: Electroencephalograph (EEG) timeseries signals are characterized by significant noise and coarse spatial resolution, which complicates the classificatio

Stabilizing Knowledge, Promoting Reasoning: Dual-Token Constraints for RLVR

arXiv:2507.15778v2 Announce Type: replace Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has become an effective post-training method for improving the reasoning abilities of Large La

researcharxiv-cs-cl

STABLE: Simulation-Ready Tabletop Layout Generation via a Semantics-Physics Dual System

arXiv:2605.16137v1 Announce Type: new Abstract: Generating simulation-ready tabletop scenes from task instructions is an intriguing and promising research direction in the field of Embodied AI. Howeve

safetyarxiv-cs-cv

STAR: A Stage-attributed Triage and Repair framework for RCA Agents in Microservices

arXiv:2605.15581v1 Announce Type: new Abstract: LLM-based root cause analysis (RCA) agents have recently emerged as a promising paradigm for incident diagnosis in microservice AIOps. However, their re

StippleDiffusion: Capacity-Constrained Stippling using Controlled Diffusion

arXiv:2605.15816v1 Announce Type: cross Abstract: Stipple patterns, point sets whose local density tracks a target image, are traditionally produced by per-density iterative optimizers, which are slow

Stochastic Compositional Optimization via Hybrid Momentum Frank--Wolfe

arXiv:2605.15350v1 Announce Type: cross Abstract: Stochastic compositional optimization minimizes objectives of the form min_{m{x} in X} F(m{f}(m{x}), m{x}), where m{f} is accessible only through nois

Stochastic Non-Smooth Convex Optimization with Unbounded Gradients

arXiv:2605.15522v1 Announce Type: cross Abstract: Much of the existing theory on first-order non-smooth optimization is built on a restrictive assumption that the gradients of the objective function a

Stock Market Prediction Using Node Transformer Architecture Integrated with BERT Sentiment Analysis

arXiv:2603.05917v3 Announce Type: replace-cross Abstract: Stock market prediction presents considerable challenges for investors, financial institutions, and policymakers operating in complex market e

Structure Abstraction and Generalization in a Hippocampal-Entorhinal Inspired World Model

arXiv:2605.15733v1 Announce Type: cross Abstract: Humans abstract experiences into structured representations to facilitate pattern inference and knowledge transfer. While the hippocampal-entorhinal (

Structure-BiEval: A Self-Supervised, Dual-Track Framework for Decoupling Structure and Content in LLM Evaluation for Web Information Systems

arXiv:2601.19923v2 Announce Type: replace-cross Abstract: As Large Language Models (LLMs) evolve into the core of Web-based autonomous agents and complex Web Information Systems, their ability to fait

Structured Jacobian Construction for Motion Optimization with High-Order Time Derivatives in Multi-Link Systems

arXiv:2605.15845v1 Announce Type: new Abstract: This paper presents a novel framework for Jacobian computation in motion optimization problems involving multi-link systems, where physical quantities a

researcharxiv-cs-ro

STS: Efficient Sparse Attention with Speculative Token Sparsity

model-releasesarxiv-cs-cl

arXiv:2605.15508v1 Announce Type: cross Abstract: The quadratic complexity of attention imposes severe memory and computational bottlenecks on Large Language Model (LLM) inference. This challenge is p

Sufficient Explanations in Databases and their Connections to Database Repairs

arXiv:2511.15623v2 Announce Type: replace-cross Abstract: We investigate the notion of sufficient explanation, and a sufficiency-degree as attribution score for database tuples in relation to query an

tutorialsarxiv-cs-ai

Local Ai

Surrogate Neural Architecture Codesign Package (SNAC-Pack)

arXiv:2605.16138v1 Announce Type: cross Abstract: Neural architecture search (NAS) is a powerful approach for automating model design, but existing methods often optimize for accuracy alone or rely on

local-aiarxiv-cs-ai

SurvivalPFN: Amortizing Survival Prediction via In-Context Bayesian Inference

model-releasesarxiv-cs-lg

arXiv:2605.15488v1 Announce Type: new Abstract: Survival analysis provides a powerful statistical framework for modeling time-to-event outcomes in the presence of censoring. However, selecting an appr

Local Ai

SwAIther-Precip: Lead-Time-Aware Bias Correction Enables Kilometer-Scale Downscaling of Global AI Precipitation Forecasts over Switzerland

arXiv:2605.16163v1 Announce Type: cross Abstract: Skillful medium-range precipitation forecasting at kilometer scale remains challenging over complex terrain because precipitation arises from multisca

local-aiarxiv-cs-lg

Symplectic Neural Operators for Learning Infinite Dimensional Hamiltonian Systems

arXiv:2605.15881v1 Announce Type: cross Abstract: The modeling and simulation of infinite-dimensional Hamiltonian systems are central problems in mathematical physics and engineering, however they pos

Syntax Without Semantics: Teaching Large Language Models to Code in an Unseen Language

arXiv:2605.15607v1 Announce Type: new Abstract: Large language models (LLMs) achieve high pass rates on code generation benchmarks, yet whether they can transfer this ability to languages absent from

researcharxiv-cs-cl

SynthRender and IRIS: Open-Source Framework and Dataset for Bidirectional Sim-Real Transfer in Industrial Object Perception

arXiv:2602.21141v2 Announce Type: replace Abstract: Object perception is fundamental for tasks such as robotic material handling and quality inspection. However, modern supervised deep-learning models

T2T-LA: A Topology-to-Topology LLM Agent for Graph Learning with Neither Feature Access nor Task Knowledge

model-releasesarxiv-cs-lg

arXiv:2512.08964v4 Announce Type: replace Abstract: Graph learning aims to convert data into graph representations, which are fundamental to many problems in machine learning for CAD, where circuits,

TACO: General Acrobatic Flight Control via Target-and-Command-Oriented Reinforcement Learning

model-releasesarxiv-cs-ro

arXiv:2503.01125v4 Announce Type: replace Abstract: Although acrobatic flight control has been studied extensively, one key limitation of the existing methods is that they are usually restricted to sp

Tadpole: Autoencoders as Foundation Models for 3D PDEs with Online Learning

model-releasesarxiv-cs-lg

arXiv:2605.15284v1 Announce Type: new Abstract: We introduce Tadpole, a novel foundation model for three-dimensional partial differential equations (PDEs) that addresses key challenges in transferabil

Agents

Talking Trees: Reasoning-Assisted Induction of Decision Trees for Tabular Data

arXiv:2509.21465v3 Announce Type: replace Abstract: Tabular foundation models are becoming increasingly popular for low-resource tabular problems. These models make up for small training datasets by p

agentsarxiv-cs-lg

Task-Semantic Graph-Driven Distributed Agent Networking for Underwater Target Tracking

arXiv:2605.15528v1 Announce Type: new Abstract: Autonomous underwater vehicle (AUV) swarms are emerging as intelligent underwater networks, where each node must sense, communicate, process local data,

safetyarxiv-cs-ro

Agents

TeamTR: Trust-Region Fine-Tuning for Multi-Agent LLM Coordination

arXiv:2605.15207v1 Announce Type: new Abstract: Multi-agent LLM systems have shown promise for complex reasoning, yet recent evaluations reveal they often underperform single-model baselines. We ident

agentsarxiv-cs-lg

TemplateRL: Structured Template-Guided Reinforcement Learning for LLM Reasoning

arXiv:2505.15692v5 Announce Type: replace Abstract: Reinforcement learning (RL) has emerged as an effective paradigm for enhancing model reasoning. However, existing RL methods like GRPO typically rel

safetyarxiv-cs-cl

Terrain Consistent Reference-Guided RL for Humanoid Navigation Autonomy

arXiv:2605.15517v1 Announce Type: new Abstract: We present a method for training reference-guided, perceptive reinforcement learning locomotion policies for humanoid robots in which reference trajecto

safetyarxiv-cs-ro

Testing properties of trees in graphical models with covariance queries

arXiv:2605.15996v1 Announce Type: cross Abstract: We consider the problem of testing properties of graphs underlying high-dimensional graphical models. We adopt the model of covariance queries introdu

Text-RSIR: A Text-Guided Framework for Efficient Remote Sensing Image Transmission and Reconstruction

arXiv:2605.15558v1 Announce Type: cross Abstract: High-resolution remote sensing imagery is critical for environmental monitoring, urban mapping, and land cover analysis, but its transmission is often

researcharxiv-cs-cv

TFZ-Tree: An Ultra-Lightweight Waveform Classification Framework for Resource-Constrained Devices

arXiv:2605.15656v1 Announce Type: cross Abstract: Under the trend of multi-waveform coexistence in 6G IoT, intelligent receivers must first identify physical-layer waveform types before performing cor

The Hardness of Achieving Impact in AI for Social Impact Research: A Ground-Level View of Challenges & Opportunities

arXiv:2506.14829v2 Announce Type: replace-cross Abstract: AI for Social Impact (AI4SI) is an emergent field harnessing interdisciplinarities between the fields of artificial intelligence (AI), machine

tutorialsarxiv-cs-ai