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Towards Graph Foundation Models for Dynamics in Complex Networked Systems: Lessons from Super-Spreader Identification in Multilayer Networks

arXiv:2606.08306v1 Announce Type: new Abstract: Network dynamics - including spreading, influence maximisation, and epidemic modelling - remain largely confined to the transductive paradigm, where mod

applicationsarxiv-cs-lg

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Towards Long-Horizon Vessel Trajectory and Destination Forecasting with Reasoning Large Language Models

DGX agent

arXiv:2606.08633v1 Announce Type: new Abstract: Long-horizon maritime trajectory prediction is important for shipping management, logistics planning, and maritime risk analysis, yet month-level foreca

model-releasesarxiv-cs-ai

9 Jun 2026

Towards Mitigating Hallucinations in Large Vision-Language Models by Refining Textual Embeddings

arXiv:2511.05017v2 Announce Type: replace Abstract: Hallucinations in Large Vision-Language Models (LVLMs) remain a persistent challenge, often stemming from inadequate integration of visual informati

safetyarxiv-cs-cv

Towards Personalized Bangla Book Recommendation: A Large-Scale Heterogeneous Book Graph Dataset

model-releasesarxiv-cs-lg

arXiv:2602.12129v2 Announce Type: replace-cross Abstract: Personalized book recommendation in Bangla literature has been constrained by the lack of structured, large-scale, and publicly available data

TQA-Bench: Evaluating LLMs for Multi-Table Question Answering

arXiv:2411.19504v2 Announce Type: replace Abstract: The advance of large language models (LLMs) has unlocked great opportunities in complex multi-modal data management tasks, particularly in question

TRACER: Token ReAssignment for Concept ERasure in Generative Recommendation

arXiv:2606.07688v1 Announce Type: cross Abstract: Generative recommendation formulates next-item prediction as autoregressive generation over semantic ID (SID) sequences derived from users' historical

Tutorials

Train at Moving Edge: Online-Verified Prompt Selection for Efficient RL Training of Large Reasoning Model

arXiv:2603.25184v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) has become essential for post-training large language models (LLMs) in reasoning tasks. While scaling rollouts can

tutorialsarxiv-cs-ai

Training-Free Generalized Few-Shot Segmentation through Open-Vocabulary Semantic Arbitration

model-releasesarxiv-cs-cv

arXiv:2606.09474v1 Announce Type: new Abstract: Generalized Few-Shot Semantic Segmentation (GFSS) has traditionally been approached as a representation-learning problem, requiring task-specific adapta

Training-Free Intelligibility-Guided Observation Addition for Noisy ASR

arXiv:2602.20967v2 Announce Type: replace-cross Abstract: Automatic speech recognition (ASR) degrades severely in noisy environments. Although speech enhancement (SE) front-ends effectively suppress b

Training-Inference Kernel Contracts: Bounding Divergence in Post-Training and Deployment

arXiv:2606.07581v1 Announce Type: cross Abstract: A modern post-training pipeline often writes one symbol for its policy, pi_theta, while evaluating it through two different programs: a training kerne

Trait-space Monitoring for Emergent Misalignment During Supervised Finetuning

arXiv:2606.07631v1 Announce Type: cross Abstract: Emergent misalignment (EM) occurs when narrow finetuning causes a model to behave dangerously outside the finetuning task. Standard training signals c

Trajectory Geometry of Transformer Representations Across Layers

arXiv:2606.09287v1 Announce Type: new Abstract: Understanding how transformer representations evolve across layers, not merely what they encode, remains an open problem in mechanistic interpretability

researcharxiv-cs-lg

Trajectory Optimization in Single and Dual-UAV Bearing-Only Target Localization

arXiv:2606.09188v1 Announce Type: cross Abstract: Bearing-only target localization is a fundamental problem in optical measurement and finds extensive applications in unmanned aerial vehicle (UAV) tec

local-aiarxiv-cs-cv

Trajectory-Refined Distillation

arXiv:2606.08432v1 Announce Type: new Abstract: On-policy distillation (OPD) has become a central post-training tool for large language models (LLMs), providing dense per-token teacher supervision alo

Transfer learning for causal forest

arXiv:2606.07693v1 Announce Type: cross Abstract: Transfer learning addresses the challenge of transfering knowledge from one domain to another. Traditional transfer learning focuses on adapting model

applicationsarxiv-cs-lg

Transforming Police-Car Swerving for Mitigating Isolated Stop-and-Go Traffic Waves: A Practice-Oriented Jam-Absorption Driving Strategy

arXiv:2602.10234v3 Announce Type: replace-cross Abstract: Stop-and-go traffic waves, a major form of freeway congestion, impose severe and persistent adverse impacts, including reduced traffic efficie

Transition-Based Digital Twin Modelling for Alzheimer's Disease under Sparse Longitudinal Data

arXiv:2606.09671v1 Announce Type: cross Abstract: Alzheimer's disease (AD) progression is highly heterogeneous and is typically observed through sparse and irregular longitudinal data, posing challeng

Agents

Traxia: A Framework for Verifiable, Agent-Native Scientific Publishing

arXiv:2606.08256v1 Announce Type: new Abstract: Verifiability, attribution, and reproducibility are foundational requirements of scientific knowledge, yet current publishing infrastructure does not en

agentsarxiv-cs-ai

TRIAGE: Dialectical Reasoning for Explainable Risk Prediction on Irregularly Sampled Medical Time Series with LLMs

arXiv:2606.09030v1 Announce Type: cross Abstract: Clinical early warning systems built on electronic health records, in which clinical observations are recorded as irregularly sampled medical time ser

TriHead-GAN: A Generative Adversarial Network with Triple-Head Discriminator for Carbon Emission Time Series Generation

model-releasesarxiv-cs-lg

arXiv:2606.07569v1 Announce Type: new Abstract: Accurate carbon emission monitoring is critical for climate policy and emerging regulatory mechanisms such as the EU Carbon Border Adjustment Mechanism,

TRL-Bench: Standardizing Cross-Paradigm Representation-Level Evaluation of Tabular Encoders

arXiv:2606.09323v1 Announce Type: new Abstract: Tabular encoders are usually evaluated inside task-specific end-to-end pipelines, so models from different training paradigms are difficult to compare d

TRUST-SCF: Transformer-based Risk Understanding and Scoring for Transactional Supply Chain Finance

arXiv:2606.08140v1 Announce Type: new Abstract: Supply Chain Finance (SCF) and LendTech platforms need credit scoring systems that respond to evolving transaction behavior, repayment delays, and activ

safetyarxiv-cs-lg

Agents

Trustworthy Smart Fabs via Professional Proxies: Scaling Safe and Sustainable by Design (SSbD) through Industrial Data Spaces

arXiv:2606.09227v1 Announce Type: cross Abstract: The convergence of the 2026 European Union Safe and Sustainable by Design (SSbD) framework, Corporate Sustainability Due Diligence Directive (CSDDD),

agentsarxiv-cs-ai

Trustworthy Visual Predicates for Robust Manipulation Understanding under Degradation

arXiv:2606.08121v1 Announce Type: new Abstract: Manipulation understanding requires reliable relational evidence, such as contact, support, containment, motion coupling, grasp, release, and active-han

researcharxiv-cs-cv

Agents

Try out Devin today! http://devin.ai

Devin is an AI software engineer developed by Cognition AI that automates coding tasks and assists with software development. The post appears to be a promotional announcement encouraging users to try

agentscognition-ai--x

TT-DAC-PS: Twin-Target Deterministic Actor-Critic with Policy Smoothing for Optimal Trade Execution

arXiv:2606.08379v1 Announce Type: new Abstract: This study addresses the optimal execution of large stock sell programs by introducing TT-DAC-PS (Twin-Target Deterministic Actor-Critic with Policy Smo

Hardware

TUDSR: Twice Upsampling-Diffusion for Higher Super-Resolution

arXiv:2606.09608v1 Announce Type: new Abstract: Diffusion-based generative models have achieved remarkable success in real-world image super-resolution (SR). With tiled diffusion techniques, these mod

hardwarearxiv-cs-cv

Turn a simple idea into a storyboard, then generate the video with Seedance 2.0. This ComfyUI workflow uses LLMs to structure prompts into s…

Turn a simple idea into a storyboard, then generate the video with Seedance 2.0. This ComfyUI workflow uses LLMs to structure prompts into storyboard-ready scenes that define how the video should play

local-aicomfyui--x

Turns out Fable 5 is shadowbanning AI researchers 🫤

researchsebastian-raschka--x

Turns out Fable 5 is shadowbanning AI researchers 🫤 mythos will be bad ON PURPOSE on ai 'frontier llm research' tasks, this is very very sad for the research community also the fact that this is un pu

TVI-CoT: Text-Visual Interleaved Chain-of-Thought Reasoning for Multimodal Understanding

arXiv:2606.08464v1 Announce Type: new Abstract: Chain-of-thought (CoT) reasoning has proven effective for enhancing problem-solving in large language models. However, when applied to multimodal LLMs (

researcharxiv-cs-cv

Two Bridges, One Pathway: From VLMs to Generalizable VLAs with Embodied Trajectory-Coupled Data

arXiv:2606.08520v1 Announce Type: new Abstract: Vision-language models (VLMs) are powerful general-purpose reasoners, yet converting them into robot control policies (VLAs) is surprisingly difficult.

safetyarxiv-cs-ro

Tyan-WP: A Wind Power Foundation Model for Ultra-Short-Term Probabilistic Forecasting

arXiv:2606.08630v1 Announce Type: cross Abstract: Global wind power capacity, especially in China, is booming, with new farms spanning diverse terrains and climates. The industry urgently needs accura

UA-DCM: Uncertainty-aware Causal Decision Making via Effect Bound Decomposition

arXiv:2601.22736v2 Announce Type: replace-cross Abstract: Causal inference from observational data can provide strong evidence for finding the best action in a decision-making scenario without having

applicationsarxiv-cs-ai

UAOR: Uncertainty-aware Observation Reinjection for Vision-Language-Action Models

arXiv:2602.18020v2 Announce Type: replace Abstract: Vision-Language-Action (VLA) models leverage pretrained Vision-Language Models (VLMs) as backbones to map images and instructions to actions, demons

applicationsarxiv-cs-cv

Hardware

Ultra Flash: Scaling Real-Time Streaming Video Generation to High Resolutions

arXiv:2606.09150v1 Announce Type: new Abstract: While recent autoregressive video diffusion models achieve remarkable streaming quality, they remain confined to low resolutions (e.g., 480P), leaving e

hardwarearxiv-cs-cv

Unambiguous Representations in Neural Networks: An Information-Theoretic Approach to Intentionality

arXiv:2512.11000v2 Announce Type: replace-cross Abstract: Representations pervade our daily experience, from letters representing sounds to bit strings encoding digital files. While such representatio

Uncertainty-Aware Hierarchical Re-Localization in OpenStreetMap via Semantic Alignment

arXiv:2603.01613v2 Announce Type: replace Abstract: Monocular re-localization enables robots to estimate camera poses from visual observations. However, many existing methods rely on dense maps or lar

safetyarxiv-cs-cv

Uncertainty-Aware Intention Prediction for Human-to-Robot Assembly Teleoperation

arXiv:2606.08341v1 Announce Type: new Abstract: In assisted teleoperation for human-robot collaboration, accurate intention prediction is critical for enabling timely and reliable robotic assistance d

researcharxiv-cs-ro

Understanding Benchmark Language Under Weakened Formal Semantics

arXiv:2509.17455v2 Announce Type: replace-cross Abstract: State-of-the-art NLP benchmarks require interpretation of natural language that specifies conditions, procedures, and exceptions, often relyin

Understanding Quantization-Aware Training: Gradients at Quantized Weights Bias to the Low-Loss Basin

arXiv:2606.09012v1 Announce Type: cross Abstract: Post-training quantization (PTQ) converts a trained full-precision model into low-bit weights without task-level retraining, while quantization-aware

local-aiarxiv-cs-ai

Understanding the Parameter Space Geometry of Transformers Encoding Boolean Functions

model-releasesarxiv-cs-lg

arXiv:2606.08768v1 Announce Type: new Abstract: Transformers consistently fail to learn certain simple functions that are provably expressible with specific parameter settings. This gap between learna

UniADC: A Unified Framework for Anomaly Detection and Classification

arXiv:2511.06644v3 Announce Type: replace Abstract: In this paper, we introduce a novel task termed unified anomaly detection and classification, which aims to simultaneously detect anomalous regions

researcharxiv-cs-cv

Unification of Closed-Open Industrial Detection Scenarios: New Large-Scale Benchmarks,Challenges and Baselines

arXiv:2606.07953v1 Announce Type: new Abstract: Large-scale Visual-Language Models (LVLMs) have achieved remarkable success in natural visual tasks, yet their application to industrial defect detectio

Unified Energy for Invariant and Independent Decoding in Diffusion Language Models

arXiv:2606.09159v1 Announce Type: cross Abstract: Diffusion Language Models (DLMs) enable parallel text generation by iteratively denoising a full sequence, offering attractive flexibility compared to

Unifying Object-Centric World Models and Diffusion Policy: A Hierarchical Framework for Multi-Stage Robotic Tasks

arXiv:2606.08775v1 Announce Type: cross Abstract: Visual world models have shown great potential in learning complex system dynamics. Recent advancements leverage these models as transition functions

UNIQ: Conformal Calibration for Adaptive Conservatism in Offline Reinforcement Learning

arXiv:2606.07592v1 Announce Type: new Abstract: Offline reinforcement learning requires careful conservatism to mitigate distribution shift, yet most existing methods apply a fixed penalty uniformly a

local-aiarxiv-cs-lg

UniQL: Towards Dialect-Universal Benchmarking for Text-to-SQL

arXiv:2606.08018v1 Announce Type: new Abstract: Existing text-to-SQL benchmarks are largely centered on SQLite, making it difficult to evaluate whether models can generalize across heterogeneous SQL d

Unsupervised Partner Design Enables Robust Ad-hoc Teamwork

arXiv:2508.06336v2 Announce Type: replace-cross Abstract: We introduce Unsupervised Partner Design (UPD), a population-free multi-agent reinforcement learning method for robust ad-hoc teamwork. UPD ge