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SLEEPING-DISCO 9M: A large-scale pre-training dataset for generative music modeling

arXiv:2506.14293v4 Announce Type: replace-cross Abstract: We present Sleeping-DISCO 9M, a large-scale pre-training dataset for music and song. To the best of our knowledge, there are no open-source hi

applicationsarxiv-cs-lg

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SlipSense: Multimodal Sensing for Online Slip Detection in Legged Robots

DGX agent

arXiv:2606.24350v1 Announce Type: new Abstract: Legged robots rely on accurate ground interaction awareness to traverse variable terrains, such as slippery surfaces. Existing slip detection methods of

researcharxiv-cs-ro

24 Jun 2026

Social Structure Matters in 3D Human-Human Interaction Generation

arXiv:2606.24255v1 Announce Type: cross Abstract: Although text-to-motion generation has achieved strong progress in synthesizing realistic single-person motions from language, extending it to text-dr

Societal Alignment Frameworks Can Improve LLM Alignment

arXiv:2503.00069v2 Announce Type: replace-cross Abstract: Recent progress in large language models (LLMs) has focused on producing responses that meet human expectations and align with shared values -

Sol Video Inference Engine: Agent-Native Full-Stack Acceleration Framework for Efficient Video Generation

arXiv:2606.23743v1 Announce Type: cross Abstract: Modern video diffusion models achieve higher generation quality through scaling, but this also increases inference cost. Although many acceleration me

agentsarxiv-cs-ai

Solving Inverse Problems of Chaotic Systems with Bidirectional Conditional Flow Matching

arXiv:2606.24824v1 Announce Type: new Abstract: Modeling chaotic systems is crucial yet challenging. Inverse problems in chaotic dynamics, namely inferring initial conditions from final states, remain

applicationsarxiv-cs-ai

Tutorials

Solving Semi-Supervised Few-Shot Learning from an Auto-Annotation Perspective

arXiv:2512.10244v2 Announce Type: replace Abstract: Semi-supervised few-shot learning (SSFSL) resembles real-world applications such as auto-annotation, as it aims to learn a model from a few labeled

tutorialsarxiv-cs-cv

SP-Mind: An Autonomous Reasoning Agent for Spatial Proteomics Analysis

arXiv:2606.24235v1 Announce Type: new Abstract: Spatial proteomics enables single-cell-resolution characterization of protein expression within tissue architecture, playing a critical role in understa

SPACE: Enabling Learning from Cross-Robot Data Toward Generalist Policies

arXiv:2606.24049v1 Announce Type: new Abstract: In robot learning, scaling training datasets across diverse embodiments and environments has become a dominant paradigm for learning generalizable robot

safetyarxiv-cs-ro

Spectral Evolution-Guided Token Pruning in Multimodal Large Language Models

arXiv:2606.24165v1 Announce Type: new Abstract: Reducing visual token redundancy is critical for accelerating Multimodal Large Language Models (MLLMs) without degrading cross-modal reasoning performan

safetyarxiv-cs-cv

Spherical-to-ERP Epipolar Rectification for Single-Axis Disparity in 360 Stereo

arXiv:2606.24847v1 Announce Type: new Abstract: Omnidirectional stereo images provide full-surround perception but violate the geometric assumptions of classical disparity estimation: in spherical or

researcharxiv-cs-cv

Stabilizing Black-Box Prompt Optimization with Textual Regularization and Signal Aggregation

arXiv:2507.09839v2 Announce Type: replace Abstract: An increasing number of NLP applications interact with large language models (LLMs) through black-box APIs, making prompt engineering critical for c

Stabilizing Physics-Informed Consistency Models via Structure-Preserving Training

arXiv:2602.09303v2 Announce Type: replace Abstract: We propose a physics-informed consistency modeling framework for solving partial differential equations (PDEs) via fast, few-step generative inferen

Statistical Foundations of LLM-based A/B Testing: A Surrogacy Framework for Human Causal Inference

arXiv:2606.17165v3 Announce Type: replace-cross Abstract: Organizations and researchers show increasing interest in using large language models (LLMs) in place of human participants in A/B tests, in t

Stochastic Expectation Maximization for Robust State-Space Radio Interferometric Imaging

arXiv:2606.23944v1 Announce Type: cross Abstract: State--space models provide a flexible framework for analyzing dynamical systems, yet they often rely on Gaussian assumptions that fail to capture hea

Structural Kolmogorov-Arnold Convolutions: Learnable Function on the Values or the Filter Shape as Parameter-Efficient Alternative to Per-Edge Convolutional KANs

arXiv:2606.24371v1 Announce Type: cross Abstract: Convolutional Kolmogorov--Arnold Networks (KANs) replace the fixed weights of a convolutional kernel with learnable univariate functions. The dominant

Local Ai

Subjective-Graph LLM Agents for Simulating Uncertainty in Classroom Social Perception

arXiv:2603.20750v2 Announce Type: replace Abstract: Social actors do not observe a common social world: each individual forms judgments from a partial and potentially distorted view of the surrounding

local-aiarxiv-cs-ai

Subtyping patients with chronic disease using longitudinal BMI patterns

arXiv:2111.05385v3 Announce Type: replace Abstract: Obesity is a major health problem, increasing the risk of various major chronic diseases, such as diabetes, cancer, and stroke. While the role of ob

Supervise What Survives: Geometry-Guided VLA Adaptation from Synthetic Robot Videos

arXiv:2606.24448v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models require large-scale video-action pairs, yet real teleoperation remains scarce. While generated robot videos offer a

researcharxiv-cs-ro

SURGELLM: Rethinking Multi-Task Evaluation through Task-Aware Feature Gating with Class-Balanced Normalization

arXiv:2606.24259v1 Announce Type: cross Abstract: Fine-tuned encoders deployed across heterogeneous NLP tasks face three compounding problems: mismatched inductive biases, class-imbalance corruption o

Synergizing Physically Constrained MCMC and Chemical-Informed Gaussian Processes for Reaction Network Discovery

arXiv:2606.23757v1 Announce Type: cross Abstract: Extracting interpretable governing equations from sparse, noisy chemical time-series data remains difficult because discrete reaction topology and con

Systematic Exploration of 4-Expert Heterogeneous Mixture-of-Experts via Automated Pipeline Search

model-releasesarxiv-cs-cv

arXiv:2606.23739v1 Announce Type: cross Abstract: We present an automated large-scale search pipeline for heterogeneous 4-Expert Mixture-of-Experts (MoE4) architectures within the LEMUR neural network

T2D-Bench: Evidence-Gated Evaluation of LLM Outputs for Type 2 Diabetes Using a Multi-Layer Clinical-Lifestyle Knowledge Graph

arXiv:2606.24145v1 Announce Type: new Abstract: Large language models (LLMs) can produce clinically fluent recommendations for type 2 diabetes while failing to satisfy guideline constraints or explici

TACTFUL: Tactile-Driven Exploration For Object Localization and Identification in Confined Environments

arXiv:2606.24712v1 Announce Type: cross Abstract: Humans effortlessly locate and identify objects by touch alone, even without vision. In contrast, robotic systems rely heavily on vision and struggle

Tutorials

Task Decomposition for Efficient Annotation

arXiv:2606.24734v1 Announce Type: cross Abstract: High-quality annotations of structured representations are expensive to collect over large corpora. Manual annotation of structure is laborious, and m

tutorialsarxiv-cs-ai

Task Vector Bases: A Unified and Scalable Framework for Compressed Task Arithmetic

arXiv:2502.01015v5 Announce Type: replace Abstract: Task arithmetic, representing downstream tasks through linear operations on task vectors, has emerged as a simple yet powerful paradigm for transfer

Ten Digits on a Train: AI-Assisted Verification of Two Eigenvalue Problems

arXiv:2606.23821v1 Announce Type: cross Abstract: Accurate numerical eigenvalues are often difficult to certify, especially in singular or non-normal settings. This article reports a human--AI collabo

Tensor-based second-order causal discovery

arXiv:2606.18074v2 Announce Type: replace-cross Abstract: Causal discovery seeks to uncover the causal dependencies among variables. For this purpose, we propose an algorithm called Tensor-based Secon

The African Language Tax: Quantifying the Cost, Latency, and Context Penalty of Tokenizing African Languages in Frontier LLMs

arXiv:2606.24460v1 Announce Type: cross Abstract: Commercial large language models bill, scale latency, and budget context per token. Yet tokenizers assign more subword tokens to the same meaning in s

The Degeneracy Distillery

model-releasesarxiv-cs-lg

arXiv:2606.23838v1 Announce Type: new Abstract: When two or more parameters or labels produce similar data, they are degenerate, or hard to distinguish. Degeneracies render both label prediction and i

The Evaluation Cost of Task Specialization in Evolutionary Multi-Robot Systems

arXiv:2606.24191v1 Announce Type: new Abstract: Task specialization can improve the efficiency of multi-robot systems (MRSs). Previous works have investigated the emergence of task-specialist robot co

researcharxiv-cs-ro

The Geometry Behind Diffusion and Flow Matching: Gradient Flows and Geodesics in Wasserstein Space

arXiv:2606.24157v1 Announce Type: new Abstract: The space P_2(R^d) of probability measures with finite second moment carries a natural geometry: the quadratic Wasserstein distance W_2 makes it a compl

The impact of generative artificial intelligence on academic development of Chinese students in humanities and social sciences

arXiv:2606.24104v1 Announce Type: cross Abstract: Generative artificial intelligence(GenAI) is reshaping learning in higher education, with particularly pronounced implications for the humanities and

applicationsarxiv-cs-ai

The Latent Bridge: A Continuous Slow-Fast Channel for Real-Time Game Agents

arXiv:2606.24470v1 Announce Type: new Abstract: A real-time agent for general computer use - with games as the most demanding case - must act within tens of milliseconds while still planning over seco

agentsarxiv-cs-ai

The mathbf{P}-Completeness of Inverted Index Traversal: On the Complexity of Evaluating Boolean Query DAGs

arXiv:2601.18747v2 Announce Type: replace-cross Abstract: Modern AI agents increasingly rely on search infrastructure to execute complex, neuro-symbolic reasoning workflows. These workflows often comp

The Measurable Majority

arXiv:2606.23853v1 Announce Type: cross Abstract: This paper studies strict majority reasoning in finite electorates using so-called extit{social decision frames}: finite sets of voters equipped with

The Professor: Multi-Teacher Unsupervised Prompt Distillation for Vision-Language Models

arXiv:2606.23897v1 Announce Type: cross Abstract: Prompt distillation compresses large vision-language models (VLMs) such as CLIP into lightweight student models by matching teacher predictions on unl

The Sparse Frontier: Sparse Attention Trade-offs in Transformer LLMs

arXiv:2504.17768v3 Announce Type: replace Abstract: Sparse attention offers a promising strategy to extend long-context capabilities in Transformer LLMs, yet its efficiency-accuracy trade-offs remain

applicationsarxiv-cs-cl

The Warrant Gap: Claim-Conditioned Re-scoring for Fact-Checking

arXiv:2606.24627v1 Announce Type: new Abstract: Fact-checking systems built on LLMs achieve high verdict accuracy on standard benchmarks, yet routinely output Supports labels whose cited evidence does

researcharxiv-cs-cl

Themis: An explainable AI-enabled framework for Reinforcement Learning with Human Feedback

arXiv:2606.24622v1 Announce Type: new Abstract: Training safe Reinforcement Learning (RL) systems is inherently challenging, with no guarantee of avoiding unwanted behaviors. The most effective defens

Thinking While Speaking: Inference-Time Knowledge Transfer for Responsive and Intelligent Conversational Voice Agents

arXiv:2511.07397v2 Announce Type: replace Abstract: Voice agents face a fundamental tension: the reasoning, retrieval, and tool use that make foundation models capable are iterative and slow, while co

agentsarxiv-cs-cl

TIGER: Taming Identity, Geometry, and Generative Priors for High-Quality Face Video Restoration

model-releasesarxiv-cs-cv

arXiv:2606.24336v1 Announce Type: new Abstract: Face Video Restoration (FVR) aims to recover high-fidelity facial videos from degraded input while preserving identity and semantic consistency across f

Local Ai

TimeLAVA: Learning-Agnostic Data Valuation for Time Series

arXiv:2606.18729v2 Announce Type: replace-cross Abstract: Data valuation quantifies the intrinsic quality of individual samples to enable principled data curation, quality control, and robust learning

local-aiarxiv-cs-lg

To Compare, or Not to Compare: On Methodological Practices in Evaluating Social Bias

model-releasesarxiv-cs-cl

arXiv:2606.24596v1 Announce Type: new Abstract: As Large Language Models are increasingly deployed in critical applications, robustly evaluating their social biases is paramount. However, the current

Token Complexity of Certifying Stochastic-Oracle Reliability

arXiv:2606.24074v1 Announce Type: cross Abstract: Wang~ite{Wang2026} introduced the Stochastic-Oracle Turing Machine (SOTM) framework and defined token complexity as the minimum expected cost of inter

Token-to-Token Alignment of Text Embeddings for Semantic Blending

arXiv:2606.24021v1 Announce Type: new Abstract: In modern generative models, images are specified and controlled through text prompts. In practice, images are generated from sequences of tokens derive

safetyarxiv-cs-cv

Topological Online Learning for Displacement-based Formation Control

arXiv:2606.23901v1 Announce Type: new Abstract: This paper addresses the problem of robust formation control by introducing Topological Online Learning for Displacement-based (TOLD) formation control,

researcharxiv-cs-ro

Toward Self-Evolution-Ready Workflow Harnesses: A Reversible Migration Path and Convertibility Taxonomy for Expert LLM Pipelines

arXiv:2606.24598v1 Announce Type: cross Abstract: While expert-validated 'LLM + script' workflows deliver significant value, they remain static: they encode hard-won domain knowledge yet fail to adapt

agentsarxiv-cs-ai