research

Thresholded Local Hyper-Flow Diffusion

arXiv:2606.09340v1 Announce Type: new Abstract: Local Hyper-Flow Diffusion (HFD) gives an edge-size-independent Cheeger-type guarantee for seeded clustering in general submodular hypergraphs, but exis

TIDE: Task-Isolated Diffusion for Unified Video Editing and Generation

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DGX agent

arXiv:2606.08260v1 Announce Type: new Abstract: Recent advances in Diffusion Transformers have driven rapid progress in video generation and editing, yet these capabilities are still handled by separa

researcharxiv-cs-cv

9 Jun 2026

Tight Sample Complexity of Transformers

arXiv:2606.09731v1 Announce Type: new Abstract: We tightly characterize the VC dimension of depth-L Transformers with a total of W parameters, mapping an input sequence of length T to a single output,

TimpaTeks: Automatic In-place Text Sequence Modification via Diffusion Language Model Steering

arXiv:2606.08408v1 Announce Type: cross Abstract: We extend activation steering to diffusion language models (DLMs) and study a novel problem that arose due to the inference mechanism of DLMs: Modifyi

Titans-as-a-Layer: Test-Time Memory for Conversational Speech Emotion Recognition

arXiv:2606.08573v1 Announce Type: new Abstract: Speech emotion recognition (SER) is commonly formulated as utterance-level classification, although conversational emotion depends on a speaker's usual

TLDR: Compressing Audio Tokens for Efficient Autoregressive Text-to-Speech

arXiv:2606.09019v1 Announce Type: cross Abstract: Codec-based autoregressive (AR) speech language models have achieved strong text-to-speech (TTS) quality by modeling speech as sequences of discrete a

Topological Neural Operators

arXiv:2606.09806v1 Announce Type: cross Abstract: We introduce Topological Neural Operators (TNOs), a principled framework for operator learning on cell complexes that lifts neural operators (NOs) fro

Toward Scalable Co-located Practical Learning: Assisting with Computer Vision and Multimodal Analytics

arXiv:2603.13679v2 Announce Type: replace-cross Abstract: Co-located practical learning leaves evidence in visible actions around patients, task resources and room zones, but these traces are often re

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

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

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

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

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

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 (

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

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 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

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

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

Unveiling Privacy Risks in Multi-modal Large Language Models: Task-specific Vulnerabilities and Mitigation Challenges

arXiv:2606.09125v1 Announce Type: cross Abstract: Privacy risks in text-only Large Language Models (LLMs) are well studied, particularly their tendency to memorize and leak sensitive information. Howe

UnWeaving the knots of GraphRAG -- turns out VectorRAG is almost enough

arXiv:2603.29875v3 Announce Type: replace-cross Abstract: One of the key problems in Retrieval-augmented generation (RAG) systems is that chunk-based retrieval pipelines represent the source chunks as

Variational Speculative Decoding: Rethinking Draft Training from Token Likelihood to Sequence Acceptance

arXiv:2602.05774v4 Announce Type: replace-cross Abstract: Speculative decoding accelerates inference for (M)LLMs, yet a training-decoding discrepancy persists: while existing methods optimize single g

Vector Space of Cycles

arXiv:2606.08202v1 Announce Type: cross Abstract: Most statistical and machine learning methods for directed interactions focus on pairwise effects among variables. Even existing cyclic models represe

vesselFM-CT: Segmenting All Blood Vessels in CT Images for System-Level Cardiovascular Analysis

arXiv:2606.09400v1 Announce Type: new Abstract: The vascular network in the human body is characterized by blood vessels exhibiting drastic structural variations in radius, length, topological propert

VFEM: Visual Feature Empowered Multivariate Time Series Forecasting with Cross-Modal Fusion

arXiv:2510.03244v2 Announce Type: replace-cross Abstract: Large time series foundation models often adopt channel-independent architectures to handle varying data dimensions, but this design ignores c

Vision-Based Early Fault Diagnosis and Self-Recovery for Strawberry Harvesting Robots

arXiv:2601.02085v3 Announce Type: replace-cross Abstract: Strawberry-harvesting robots faced challenges such as poor visual perception, gripper misalignment, empty grasp/misgrasp, and slippage, which

We trained language models that compress massive contexts into tiny latent representations. Latent Context Language Models (LCLMs) outperfor…

We trained language models that compress massive contexts into tiny latent representations. Latent Context Language Models (LCLMs) outperform existing KV cache compression methods on the latency/accur

researchyann-lecun--x

Wedge Sampling: Efficient Tensor Completion with Nearly-Linear Sample Complexity

arXiv:2602.05869v2 Announce Type: replace-cross Abstract: We introduce Wedge Sampling, a new non-adaptive sampling scheme for low-rank tensor completion. We study recovery of an order-k low-rank tenso

Weighted universal approximation of differentiable maps on infinite-dimensional manifolds

arXiv:2606.09820v1 Announce Type: cross Abstract: We generalize the universal approximation theorem for functional input neural networks (FNN) to differentiable maps by including the approximation of

What Makes Video World Model Latents Action-Relevant: Prediction over Reconstruction

arXiv:2606.07687v1 Announce Type: cross Abstract: Video world models are increasingly used to provide predictive visual representations, yet it remains unclear which pretraining signals induce action-

What neurosurgeons need to see: synthetic intra-operative MRI from ultrasound for brain-shift compensation in brain tumour surgery

arXiv:2606.07658v1 Announce Type: new Abstract: Maximal safe resection is the primary objective in glioma surgery. Neuronavigation guidance is progressively degraded by brain shift after dural opening

What the Eyes See, the LLMs Miss: Exploiting Human Perception for Adversarial Text Attacks

arXiv:2606.09700v1 Announce Type: cross Abstract: Large language model (LLM)-powered content moderation systems have become a critical defense against harmful online content. However, these systems pr

What's the Point? Spatial Grammar & Index Resolution for Sign Language Processing

arXiv:2606.08056v1 Announce Type: cross Abstract: Sign language models are predominantly trained with gloss-sequence or text supervision, thereby under-modeling non-lexical and productive construction

When Are Neural Interaction Discoveries Real? Identifiability, Recoverability, and a Pre-Fit Diagnostic

arXiv:2606.08390v1 Announce Type: new Abstract: When a neural time-series model reports that one variable modulates another's effect on a target, is the discovered interaction a property of the data o

When Does Delegation Beat Majority? A Delegation-Based Aggregator for Multi-Sample LLM Inference

arXiv:2606.08098v1 Announce Type: new Abstract: Majority voting over sampled answers is the dominant unsupervised aggregator for multi-sample LLM inference. We show that piping the signals every sampl

When No Answer Is Correct: Diagnosing Absent Answer Detection for MLLMs in Video Understanding

arXiv:2606.08239v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have made substantial advancements in video understanding, yet the reliability of their responses remains under

Where the Score Lives: A Wavelet View of Diffusion

arXiv:2606.08309v1 Announce Type: cross Abstract: Score-based generative models have had remarkable success over the last decade in generating a diverse set of visually plausible images. A variety of

Why Limit the Residual Stream to Layers and Not Tokens? Persistent Memory for Continuous Latent Reasoning

arXiv:2606.07720v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated remarkable reasoning abilities on mathematical and multi-hop planning tasks. The CoCoNuT (Chain of Contin

Zero Touch Predictive Orchestration: Automating Time-Series Models for the Cloud-Edge Continuum

arXiv:2606.09787v1 Announce Type: new Abstract: The Cloud-Edge Continuum (CEC) enables latency-critical applications by distributing resources to the far edge, but its extreme volatility makes proacti

A Conformation-Centric Generative Foundation Model for Linear Polymer Modeling and Design

arXiv:2510.16023v2 Announce Type: replace Abstract: Linear polymers, macromolecules formed from monomers covalently bonded into continuous chains, underpin countless technologies and are indispensable

A Multi-Operator Mixed-Reality Interface for Multi-Robot Control and Coordination: Co-Located and Private Workspace Collaboration

arXiv:2606.07013v1 Announce Type: new Abstract: Multi-operator control of robot teams requires not only access to the same mission information, but also mechanisms for maintaining shared awareness and

researcharxiv-cs-ro

A Study of Parallel Continuous Local Search

arXiv:2606.06656v1 Announce Type: new Abstract: We study parallel Continuous Local Search (CLS) as a solution approach for Boolean satisfiability problems with symmetric pseudo-Boolean (PB) constraint

Ablation Study of Block Size, Weight Precision, and Scale Precision in NVFP4 Inference for Low-Power Edge-Efficient Neural Networks

arXiv:2606.06527v1 Announce Type: cross Abstract: Energy-efficient edge inference requires reducing arithmetic cost, memory traffic, and hardware overhead. This paper presents an ablation-focused stud

Accelerated Decentralized Stochastic Gradient Descent for Strongly Convex Optimization

arXiv:2606.07496v1 Announce Type: new Abstract: Decentralized stochastic optimization is a fundamental paradigm for large-scale learning over networks, where agents communicate only with their neighbo

Accelerating Reproducible Research in Synthetic EHR Generation

arXiv:2606.06990v1 Announce Type: new Abstract: The generation of high-fidelity synthetic Electronic Health Records (EHR) is crucial for advancing medical research while preserving patient privacy. Ho

Adaptive Band Selection for Hyperspectral Classification with Spatially Disjoint Evaluation

arXiv:2606.06684v1 Announce Type: new Abstract: Hyperspectral band selection methods based on differentiable selectors can be sensitive to initialization and to extracting a final discrete subset, whi

Advanced Flood Prediction with Physics-Guided Deep Learning: Combining UNet, FNO, and SAR/Optical Imagery

arXiv:2606.06524v1 Announce Type: cross Abstract: Accurate and scalable flood mapping remains challenging due to limited ground observations, heterogeneous terrain conditions, and the difficulty of en