Search: “research”

StableWorld: Towards Stable and Consistent Long Interactive Video Generation

arXiv:2601.15281v2 Announce Type: replace Abstract: In this paper, we explore the overlooked challenge of stability and temporal consistency in interactive video generation, which synthesizes dynamic

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Research

Stop Before You Fail: Operational Capability Boundaries for Mitigating Unproductive Reasoning in Large Reasoning Models

DGX agent

arXiv:2509.24711v4 Announce Type: replace Abstract: Current answering paradigms for Large Reasoning Models (LRMs) often fail to account for the fact that some questions may lie beyond the model's oper

researcharxiv-cs-ai

1 Sept 2026

Stream-DiffVSR: Low-Latency Streamable Video Super-Resolution via Auto-Regressive Diffusion

arXiv:2512.23709v3 Announce Type: replace Abstract: Diffusion-based video super-resolution (VSR) methods deliver strong perceptual quality but are often unsuitable for latency-sensitive scenarios due

Strengthening Recursive Constructions for Zero-Error Shannon Capacity

arXiv:2608.30273v1 Announce Type: cross Abstract: The exact Shannon capacity is unknown for every odd cycle beyond the five-cycle C_5, making odd cycles a central open problem in zero-error informatio

Stride-k Subsampling: Train-Free Audio Token Reduction for Whisper

arXiv:2608.30927v1 Announce Type: cross Abstract: Whisper exposes speech through a fixed 1500-token encoder interface, now a default representation for ASR decoders and Whisper-based speech language m

Structured State Reconciliation for Human-AI Task Handover

arXiv:2608.28907v1 Announce Type: cross Abstract: Task handover requires communicating enough current state for a successor to resume work, yet the relevant information is often divided between system

Super4DR: 4D Radar-centric Self-supervised Odometry and Gaussian-based Map Optimization

arXiv:2512.09608v2 Announce Type: replace Abstract: Conventional odometry and mapping methods using visual or LiDAR data often struggle under poor illumination and adverse weather conditions. Although

researcharxiv-cs-ro

Supraglacial Lake Fate Is Knowable Long Before the Season Ends

arXiv:2608.30113v1 Announce Type: new Abstract: A supraglacial lake on the Greenland Ice Sheet ends its melt season in one of four ways: it drains rapidly through a hydrofracture, drains slowly across

T3S: Improving Multi-Task Reinforcement Learning with Task-Specific Feature Selector and Scheduler

arXiv:2608.30765v1 Announce Type: new Abstract: Multi-task reinforcement learning (MTRL) is a technique to train multiple tasks simultaneously, where previous works usually train a single model to sol

Tail-Replay: Escaping the Curse of Linear Attention in Prefix Caching for Hybrid LLMs

arXiv:2608.30310v1 Announce Type: cross Abstract: Hybrid large language models interleave full-attention layers with linear-attention layers to reduce the cost of long-context inference. This structur

Taking the Whys Seriously: Limitations of Counterfactual Explanations in Justification and Recourse

arXiv:2608.30956v1 Announce Type: cross Abstract: Counterfactual explanations (CEs) are widely used in explainable artificial intelligence (AI) to show how a model's outputs would change if the input

TaxCE : A Framework for Automated Taxonomy Construction and Evaluation at Scale

arXiv:2608.30614v1 Announce Type: new Abstract: Organizing unstructured feedback text into hierarchical taxonomy is a fundamental challenge in NLP, particularly in domains where feedback arrives at ma

Temperature-Adaptive Transformed Teacher Matching

arXiv:2608.29099v1 Announce Type: cross Abstract: Temperature scaling is a core component of knowledge distillation, yet its role and effect are still not fully understood. Transformed Teacher Matchin

Temporal Analysis of NetFlow Datasets for Network Intrusion Detection Systems

arXiv:2503.04404v3 Announce Type: replace Abstract: This paper investigates the temporal analysis of NetFlow datasets for machine learning (ML)-based network intrusion detection systems (NIDS). Althou

Test of partial effects for Frechet regression on Bures-Wasserstein manifolds

arXiv:2506.23487v2 Announce Type: replace-cross Abstract: We propose a novel test for assessing partial effects in Frechet regression with responses lying on the Bures-Wasserstein manifold. Under the

Test-Time Scaling for Video Diffusion Models via Diagnosis-Guided Candidate Recycling

arXiv:2608.29322v1 Announce Type: new Abstract: Recent video diffusion models have achieved remarkable generation quality, but high-fidelity results still largely depend on closed-source systems or co

Text-Driven Artistic Staging: Pose, Lighting, and Camera References from Paintings

arXiv:2608.28823v1 Announce Type: cross Abstract: Artists coordinate human pose, illumination, and camera placement to convey narrative and emotion, but existing generative methods typically model the

Text-Guided Diffusion-Based Adversarial Attacks on Chest X-Ray Images

arXiv:2608.29456v1 Announce Type: new Abstract: As artificial intelligence is increasingly integrated into chest X-ray (CXR) interpretation, triage, and clinical decision support, understanding its vu

The Depth Flow of Token Representations Is Nonlinear and Does Not Descend Its Own Density

arXiv:2608.29706v1 Announce Type: new Abstract: A token's representation is carried through the network layer by layer. The whole vocabulary carried together forms a flow. We fit this flow's equation

The Emergent Symbolic Structure of Artificial Neural Networks

arXiv:2608.29530v1 Announce Type: cross Abstract: Modern systems in artificial intelligence (AI) somehow excel in domains for which they seem poorly suited. Intelligence has traditionally been modeled

The Hallucination Signal Is a Mean Shift: Why Simple Probes Suffice

arXiv:2608.28930v1 Announce Type: cross Abstract: Hidden-state probes effectively detect LLM hallucinations, but the geometry of the signal remains poorly characterized, driving increasingly complex p

The information geometry of product-reference discrete diffusion: Interaction growth complexity and optimal scheduling

arXiv:2608.28949v1 Announce Type: cross Abstract: We study a class of product-reference diffusion algorithms for sampling from a discrete distribution. We show that their sampling performance can be c

The Language of the Question Selects the Market: Query Language and Exit IP as Separable Factors in Commercial Recommendations from a Generative Search Interface

arXiv:2608.30052v1 Announce Type: cross Abstract: When a generative search interface answers a commercial question, which market's products it names is decided before the model reasons about the produ

The Nearest Target Is the Wrong One: Target Separation in Arc2Face Identity Unlearning

arXiv:2608.30087v1 Announce Type: new Abstract: Unlearning an identity from a face-conditioned generator by redirecting its conditioning embedding can silently fail if the redirected output is still v

The Structure of Merging Turbulent Jets Beneath a Small Quadrotor

arXiv:2608.30900v1 Announce Type: cross Abstract: The downwash wake of a hovering quadrotor governs both the vehicle's own performance and the safe spacing of multi-rotor formations. Prior measurement

researcharxiv-cs-ro

The Value of Depth in Message Passing on Sparse Graphs: A Kesten-Stigum Dichotomy

arXiv:2607.16676v2 Announce Type: replace-cross Abstract: How deep does a graph neural network need to be on a sparse graph? We study its purest statistical form: node classification on the sparse con

ThermoSplat: Cross-Modal 3D Gaussian Splatting with Feature Modulation and Geometry Decoupling

arXiv:2601.15897v3 Announce Type: replace Abstract: Multi-modal scene reconstruction integrating RGB and thermal infrared data is essential for robust environmental perception across diverse lighting

Think, Look, and Revise: Inconsistency-Aware Visual Self-Correction in MLLMs

arXiv:2608.29374v1 Announce Type: new Abstract: Tool-augmented multimodal reasoning integrates external tools (e.g., object detection, depth estimation) into multimodal large language models (MLLMs) t

Three Steps at a Time: Learning Representations from Action Sequences in Contrastive RL

arXiv:2608.30640v1 Announce Type: new Abstract: While self-supervised approaches to reinforcement learning have achieved strong results by learning representations of states and actions, a key open qu

To Copy or Not to Copy: Copying Is Easier to Induce Than Recall

arXiv:2601.12075v2 Announce Type: replace Abstract: Language models used in retrieval-augmented settings must arbitrate between parametric knowledge stored in their weights and contextual information

Toward Generalizable Deep Learning Based Peatland Fire Detection via Walsh Hadamard Transform and Domain Adaptation

arXiv:2603.02465v2 Announce Type: replace-cross Abstract: Machine learning-based wildfire detection has advanced significantly using deep learning models trained on large wildfire image and video data

Toward Latent Language Model Skills Steering and Optimization: An Empirical Study

arXiv:2608.29459v1 Announce Type: new Abstract: Skills, as a useful abstraction for the procedural capabilities of large language models (LLMs), capture how models perform structured, multi-step reaso

Towards Accurate and Lightweight Peripheral Neuroblastic Tumor Diagnosis via Contrastive Multi-scale Pathological Image Analysis

arXiv:2504.13754v4 Announce Type: replace-cross Abstract: Peripheral neuroblastic tumors (pNTs) are among the most common extracranial solid tumors in children, and accurate pathological subtyping is

Towards an Expressivity-Normalized Energy-Demand Comparison of ANNs and SNNs

arXiv:2608.29869v1 Announce Type: new Abstract: Spiking neural networks (SNNs) are often regarded as energy-efficient alternatives to artificial neural networks (ANNs), yet their advantage depends cri

Towards Cognitive Process-Aware Proactive Writing Support

arXiv:2608.30424v1 Announce Type: cross Abstract: Large language models can support writing, but existing tools require users to explicitly articulate prompts-particularly burdensome in creative writi

TPSO: Training-Free Diverse Image Generation via Semantic Prompt Embedding Optimization

arXiv:2511.19811v2 Announce Type: replace-cross Abstract: Image diversity remains a fundamental challenge for text-to-image diffusion models. Low-diversity generation often leads to repetitive outputs

TPvG: A Moral Decision Framework for Large Language Models from One-Shot to Sequential Feedback

arXiv:2608.28610v1 Announce Type: new Abstract: Existing LLM moral evaluations typically present models with isolated moral vignettes and elicit a single-shot decision, neglecting a factor known to pr

Tracing Generated Samples to Training-Data Clusters in Flow-Matching Models

arXiv:2608.30081v1 Announce Type: cross Abstract: Understanding which training samples influence a generated image is an important problem in generative modeling. In flow matching, training samples in

Training-free LLM Verification via Recycling Few-shot Examples

arXiv:2506.17251v3 Announce Type: replace-cross Abstract: Although large language models (LLMs) have achieved remarkable performance, the inherent stochasticity of their reasoning processes and varyin

Tutorials

Transformer-Based Flow Shop Scheduling Using MILP-Generated Training Data

arXiv:2608.29690v1 Announce Type: cross Abstract: Advances in machine learning (ML) have created new opportunities to complement traditional operations research (OR) methods. In particular, transforme

tutorialsarxiv-cs-lg

Triggering Chain-of-Thought via Latent Feature Interventions in Large Language Models

arXiv:2601.08058v2 Announce Type: replace-cross Abstract: Chain-of-Thought (CoT) prompting often improves the reasoning performance of large language models (LLMs), but the internal signal that trigge

Trust Under Siege: Label Spoofing Attacks against Machine Learning for Android Malware Detection

arXiv:2503.11841v2 Announce Type: replace-cross Abstract: Machine Learning (ML) malware detectors rely heavily on crowd-sourced AntiVirus (AV) labels, with platforms like VirusTotal serving as trusted

Uncertainty-Aware End-to-End AI Weather Forecasting: Disentangling Observation and Model Contributions

arXiv:2608.30795v1 Announce Type: cross Abstract: End-to-end weather forecasting systems produce skillful global gridded and station forecasts directly from raw Earth observations, replacing the numer

Uncertainty-Aware Multi-Task Learning for Joint Modulation Recognition and SINR Estimation

arXiv:2608.28865v1 Announce Type: cross Abstract: Joint modulation recognition and signal-to-interference-plus-noise ratio (SINR) estimation can reduce duplicated processing in intelligent receivers,

Uncertainty of Vision Medical Foundation Models

arXiv:2608.30390v1 Announce Type: new Abstract: Accurate uncertainty estimation is essential for machine learning systems de- ployed in high-stakes domains such as medicine. Traditional approaches pri

Understanding Deep Learning via Notions of Rank

arXiv:2408.02111v4 Announce Type: replace-cross Abstract: Despite the extreme popularity of deep learning in science and industry, its formal understanding is limited. This thesis puts forth notions o

Understanding Temporal Semantic Stability in Open-Vocabulary UAV Perception through Metric 3D Fusion

arXiv:2608.28665v1 Announce Type: new Abstract: Recent open-vocabulary segmentation models have advanced semantic perception for UAVs, but predictions from moving aerial platforms can remain temporall

Unveiling Language Routing Isolation in Multilingual MoE Models for Interpretable Subnetwork Adaptation

arXiv:2604.03592v2 Announce Type: replace-cross Abstract: Mixture-of-Experts (MoE) models exhibit striking performance disparities across languages, yet the internal mechanisms driving these gaps rema