All entries

Stokes-Informed Diffusion for Robust Linear Polarization Estimation

arXiv:2607.21239v1 Announce Type: new Abstract: Polarization cues benefit applications such as material detection and de-reflection, yet acquiring them typically requires dedicated hardware. This moti

safetyarxiv-cs-cv

Agents

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Streaming Multi-Agent Autoregressive Diffusion Model with World State Registers

DGX agent

arXiv:2607.21594v1 Announce Type: new Abstract: Multi-agent interactive world models should not only generate consistent observations, but also maintain world states that persist across agents and evo

agentsarxiv-cs-cv

24 Jul 2026

StrideDiffusion: Accelerating Diffusion Models for Time-series Generation

arXiv:2607.20545v1 Announce Type: new Abstract: Diffusion models have become competitive generators for time series, but their practical use is limited by the large number of sequential denoising step

Structure-Preserving Physics-Informed Neural Network for the Korteweg--de Vries (KdV) Equation

arXiv:2511.00418v2 Announce Type: replace Abstract: Physics-Informed Neural Networks (PINNs) offer a flexible framework for solving nonlinear partial differential equations (PDEs), yet conventional im

Student-Centered Distillation Narrows the Agentic Gap Between Small and Large LLMs

arXiv:2509.14257v3 Announce Type: replace-cross Abstract: Large Language Model agents achieve strong performance on multi-step reasoning and tool-use tasks, but their impressive capabilities typically

SubSplat: High-Resolution Pixel-aligned 3DGS via Sub-pixel Gaussian Reparameterization

arXiv:2607.20813v1 Announce Type: new Abstract: Pixel-aligned Gaussian splatting enables efficient and generalizable novel-view synthesis. However, high-resolution rendering faces a critical trade-off

researcharxiv-cs-cv

SuperFlow: Training Flow Matching Models with RL on the Fly

arXiv:2512.17951v3 Announce Type: replace Abstract: Recent progress in flow-based generative models and reinforcement learning (RL) has improved text-image alignment and visual quality. However, curre

safetyarxiv-cs-cv

Surprisal Theory is Tautological (without Rational Grounding)

arXiv:2607.21574v1 Announce Type: new Abstract: Surprisal theory holds that the human processing difficulty of a linguistic unit in context is an affine function of its surprisal under some language m

researcharxiv-cs-cl

Synthetic data generation framework for quality control automation in gravure printing

arXiv:2607.21577v1 Announce Type: cross Abstract: Quality control in printing, particularly in rotogravure printing, still depends on slow, costly, and subjective manual inspection. Automated surface

applicationsarxiv-cs-ai

Synthetic minority data is redundant or invalid: a data-dependent validity theory and a de-biased test

arXiv:2607.20787v1 Announce Type: cross Abstract: For two decades, the standard remedy for class-imbalanced learning has been to fabricate synthetic minority examples, and the standard evidence of the

safetyarxiv-cs-ai

T-STAR: A Large-Scale Benchmark for Spatio-Temporal Panoptic Scene Graph Generation in Satellite Video

model-releasesarxiv-cs-cv

arXiv:2607.21228v1 Announce Type: new Abstract: Structured understanding of satellite video is essential for advancing dynamic geospatial scene analysis from low-level perception to high-level cogniti

TableVerse: A Large-scale Tabletop Dataset with Real-world Grounded Layouts for Generalizable Manipulation

arXiv:2607.21017v1 Announce Type: new Abstract: The development of generalizable robotic manipulation policies is inherently bounded by the availability of large-scale, high-fidelity scene data. While

applicationsarxiv-cs-ro

TabPFN beyond Tabular Data: Calibration and Accuracy on Multimodal Embeddings

arXiv:2607.11007v2 Announce Type: replace Abstract: Few-shot multimodal classification commonly attaches a lightweight head, such as k-nearest neighbors, logistic regression, or a linear SVM, to a fro

Tackling Heterogeneity in Federated Learning via Variance-Reduced Boltzmann Sampling within Homogeneous Social Coalitions

arXiv:2506.02897v3 Announce Type: replace Abstract: Federated Learning (FL) enables privacy-preserving collaborative model training, but its effectiveness is often limited by client data heterogeneity

Agents

TeaRAG: A Token-Efficient Agentic Retrieval-Augmented Generation Framework

arXiv:2511.05385v2 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) utilizes external knowledge to augment Large Language Models' (LLMs) reliability. For flexibility, agenti

agentsarxiv-cs-ai

Telco-GAIA: Bilingual Benchmark for Agents in Telecom Domain

arXiv:2607.20510v1 Announce Type: new Abstract: We introduce Telco-GAIA, a bilingual, multi-modal benchmark for evaluating tool-using agents on the data of a real-world telecommunications operator. Te

Tencent WorkBuddy Bench: A Multi-Domain Coding-Agent Benchmark with Contamination-Resistant Task Construction

model-releasesarxiv-cs-cl

arXiv:2607.20911v1 Announce Type: new Abstract: We introduce Tencent WorkBuddy Bench, a multi-domain evaluation suite for coding agents; this report documents its construction methodology, scoring pro

Local Ai

Test-Time Scaling via Error Localization

arXiv:2607.21453v1 Announce Type: new Abstract: Scaling inference-time computation has emerged as a reliable method to improve the performance of large language models on complex reasoning and program

local-aiarxiv-cs-lg

Texture++: Elevating 3D Asset Texture Resolution with a Region-Aware Diffusion Model

arXiv:2607.21504v1 Announce Type: new Abstract: Numerous 3D assets are discarded due to low texture resolution, while current super-resolution models ignore texture maps and focus on natural images. A

researcharxiv-cs-cv

thaulab@EEUCA 2026: Who Said What to Whom? A Targeting-Aware Neural-Symbolic Pipeline for Gaming Toxicity Detection

arXiv:2607.20447v1 Announce Type: new Abstract: This paper describes our system for the EEUCA 2026 Shared Task on toxicity classification in gaming chat. We implement a three-stage pipeline combining

safetyarxiv-cs-cl

The Active Ingredient in Muon's Grokking

arXiv:2607.20512v1 Announce Type: cross Abstract: The Muon optimizer reaches the grokking threshold on modular arithmetic faster than AdamW. Prior work attributes this to 'spectral-norm constraints pl

The Boundaries of Automation: A Theory of Persistent Human Participation

arXiv:2607.21547v1 Announce Type: new Abstract: The rapid progress of AI has intensified the long-standing pursuit of automation: replacing human participation with algorithms wherever possible. Impli

applicationsarxiv-cs-ai

The Dark Room in the Reward Channel: Dense Prediction Rewards Collapse GRPO-Trained LLM Agents -- and What Actually Works

arXiv:2607.21273v1 Announce Type: new Abstract: Dense per-step supervision is an appealing remedy for sparse-reward, long-horizon LLM agents: reward the agent for predicting its next observation, and

safetyarxiv-cs-lg

The Devil is in the Spectrum: Mitigating Representation Collapse in LLMs via Topologically Regularized Side-Path

arXiv:2607.20484v1 Announce Type: new Abstract: Large Language Models (LLMs) are fundamentally limited by representation collapse, a bottleneck that severely degrades long-context performance. We iden

The Geometry of Personality: Activation Steering with Jungian Cognitive Functions

arXiv:2607.20803v1 Announce Type: cross Abstract: Activation steering enables control and interpretation of LLMs, yet existing work primarily models personality through static trait frameworks such as

The Hidden Footprint: Making Storage a First-Class Metric for LLM Agent Evaluation

arXiv:2607.11149v3 Announce Type: replace Abstract: LLM agent benchmarks measure task completion, reliability, and inference cost, but not the persistent data an agent run leaves on disk, including lo

The Human-AI Substitution Principle: When will you be replaced by AI in your organization?

arXiv:2607.20781v1 Announce Type: new Abstract: Artificial Intelligence (AI) is rapidly transforming organizations, raising a fundamental organizational and economic question: when will a human employ

The Price of Hidden Curvature: An widetilde{Omega} (d^{5/4} sqrt{T}) Lower Bound for Bandit Convex Optimization

arXiv:2607.18652v2 Announce Type: replace-cross Abstract: We establish a widetildeOmega(d^{5/4}sqrt T) lower bound on the minimax expected regret of stochastic bandit convex optimization of 1-Lipschit

The RealDefocus Benchmark for Defocus Deblurring

model-releasesarxiv-cs-cv

arXiv:2607.21078v1 Announce Type: new Abstract: Single-Image Defocus Deblurring (SIDD) aims to recover an all-in-focus image from a single defocused observation, but rigorous and reproducible evaluati

The Second LoViF 2026 Challenge on Real-World All-in-One Image Restoration: Methods and Results

model-releasesarxiv-cs-cv

arXiv:2607.21118v1 Announce Type: new Abstract: This paper presents a review of the second LoViF Challenge on Real-World All-in-One Image Restoration. The challenge aims to advance unified image resto

The Storyteller in the Model: Narrative Pattern Inheritance, Escalation Dynamics, and Alignment Governance in LLMs

arXiv:2607.20449v1 Announce Type: cross Abstract: LLMs are trained predominantly on human-authored text, yet the structural and narrative conventions embedded in that text are rarely examined as a sou

safetyarxiv-cs-ai

The Weight of Silence: A Causal Case for Weights Over the Scratchpad in Latent Chess Reasoning

arXiv:2607.20952v1 Announce Type: cross Abstract: Latent, or silent, reasoning lets language models carry out intermediate computation in continuous vector space instead of words, and is widely assume

researcharxiv-cs-cl

Thermodynamic Weight Decay: Exploring Grokking Acceleration via Attention Specific Heat

arXiv:2607.20552v1 Announce Type: new Abstract: Grokking -- the delayed generalization of neural networks long after they have memorized their training data -- wastes thousands of training epochs and

Thinkink: 2D Spatial Ink-native Interaction with LLMs

arXiv:2607.21468v1 Announce Type: cross Abstract: People often use handwritten notes and sketches to externalize ideas for ideation. To integrate large language models (LLMs) into this practice, we pr

THOR: A Theta-Gamma Hierarchical Oscillatory Reasoning Framework for Multi-hop QA

arXiv:2607.20459v1 Announce Type: cross Abstract: Multi-hop question answering requires retrieving and integrating evidence from multiple contexts. Despite the rapid progress of current research, mult

Three-Pronged Spectral Control for Federated Parameter Efficient Fine Tuning

arXiv:2607.20914v1 Announce Type: new Abstract: Federated parameter-efficient fine-tuning (PEFT) enables communication-efficient adaptation of large pretrained models on decentralized edge data, but i

Through-the-Earth Magnetic Induction Communication and Networking: A Comprehensive Survey

arXiv:2510.14854v4 Announce Type: cross Abstract: Magnetic induction (MI) communication (MIC) has emerged as a promising candidate for underground communication networks due to its excellent penetrati

Token Budget Saturation and Mechanistic Early Detection of Reasoning Non-Convergence in Chain-of-Thought Models

arXiv:2607.21433v1 Announce Type: cross Abstract: Chain-of-thought reasoning models such as DeepSeek-R1-Distill-Qwen-7B exhibit a bimodal convergence pattern: generations either terminate within a tok

Token-Level Entropy Reveals Demographic Disparities in Large Language Models

arXiv:2501.19337v5 Announce Type: replace Abstract: A name alone measurably reshapes a language model's next-token distribution before a single token is sampled. We measure full-vocabulary Shannon ent

safetyarxiv-cs-cl

TopoGuard: Graph Theory Based Defenses Against Split-Knowledge Attacks on RAG

arXiv:2607.20437v1 Announce Type: new Abstract: Production Retrieval Augmented Generation (RAG) systems rely on aggregating multiple external documents to answer complex queries. However, the retrieve

applicationsarxiv-cs-cl

TOPReward: Token Probabilities as Hidden Zero-Shot Rewards for Robotics

arXiv:2602.19313v2 Announce Type: replace-cross Abstract: General-purpose robot learning requires dense, instruction-conditioned feedback that can distinguish meaningful task progress from stalled, fa

torchsom: The Reference PyTorch Library for Self-Organizing Maps

arXiv:2510.11147v2 Announce Type: replace-cross Abstract: This paper introduces torchsom, an open-source Python library that provides a reference implementation of the Self-Organizing Map (SOM) in PyT

TOUR: A Trajectory-Level Unlearning Benchmark for Offline Reinforcement Learning

arXiv:2607.21111v1 Announce Type: cross Abstract: Offline Reinforcement Learning (RL) agents are trained on fixed behavioral trajectories, which makes trajectory-level deletion important when selected

Local Ai

Toward Continuous Assurance for the Democratization of AI Agent Creation in Industry

arXiv:2607.21495v1 Announce Type: new Abstract: AI agents are increasingly created inside organizations by non-engineering users through low-code, no-code, and conversational development environments.

local-aiarxiv-cs-ai

Toward cryptographically verifiable authorization for autonomous AI agents: A security hypothesis, preliminary formal model, and proof-of-concept implementation

arXiv:2607.21325v1 Announce Type: cross Abstract: Autonomous AI agents increasingly execute actions, invoke tools, and operate on protected resources with limited human oversight. Existing authenticat

safetyarxiv-cs-ai

Toward Generalizable Cognitive Impairment Detection with Speech-Based Multimodal Large Language Models

arXiv:2607.21496v1 Announce Type: cross Abstract: Cognitive impairment (CI) is a growing public health concern. Early and accurate diagnosis is critical for enabling timely intervention and improving

Toward Mechanistic Interpretability of an AI Foundation Model Fine-Tuned for Atmospheric Chemistry

arXiv:2607.20778v1 Announce Type: new Abstract: Weather forecasting foundation models (FMs) are increasingly fine-tuned to predict air quality, offering fast global pollution forecasts at lower comput

Towards a Certifying Grounder

arXiv:2607.21199v1 Announce Type: cross Abstract: Grounding, the translation of high-level theories into equivalent quantifier-free formulas, is a crucial step in declarative solving, yet it has so fa