Search: “research”

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

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Research

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

DGX agent

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

researcharxiv-cs-ai

9 Jun 2026

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

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

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

AI Level of Detail: Distance-Aware ML Model Precision Selection for Real-Time Human Motion Prediction in Games

arXiv:2606.06565v1 Announce Type: cross Abstract: Modern game engines spend significant compute animating NPCs with learned motion models. This paper proposes AI Level of Detail (AI LOD), a framework

AI Sovereignty: A Qualitative Model of Strategic Competition as AI Becomes an Instrument of National Power

arXiv:2606.07245v1 Announce Type: cross Abstract: AI sovereignty is the extent to which a nation independently controls its artificial intelligence (AI) technologies. The race toward ever-more-sophist

“AIでAIを開発”加速へ Sakana AI 「計算資源の量ではなく、アイデアで進歩」 https://www.itmedia.co.jp/aiplus/article/2606/08/2000000068/

Sakana AI founder David Ha discusses how AI can accelerate AI development, emphasizing that progress comes from innovative ideas rather than computational resource quantity alone. The article covers S

researchdavid-ha--x

AIDEN: Design and Pilot Study of an AI Assistant for the Visually Impaired

arXiv:2511.06080v4 Announce Type: replace Abstract: This paper presents AIDEN, an artificial intelligence-based assistant designed to enhance the autonomy and daily quality of life of visually impaire

An Expanded Synthetic Conversation Dataset for Multi-Turn Smishing Detection

arXiv:2606.06879v1 Announce Type: new Abstract: Our prior work introduced COVA, a synthetically generated multi-turn conversational smishing dataset of 3,201 labeled conversations, establishing baseli

researcharxiv-cs-cl

Analysing Differences in Persuasive Language in LLM-Generated Text: Uncovering Stereotypical Gender Patterns

arXiv:2601.05751v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly used for everyday communication tasks, including drafting interpersonal messages intended to inf

Anchored, Not Graded: Vision-Language Models Fail at Slant-from-Texture Perception

arXiv:2606.06714v1 Announce Type: new Abstract: Human perception of surface slant from texture exhibits systematic, graded biases that emerge reliably in psychophysical experiments. Prior work showed

Applying Deep Learning for cockpit segmentation in the context of mixed reality

arXiv:2606.06520v1 Announce Type: new Abstract: Computer vision is an area that has been growing continuously. With the advance of technologies with a first-person view, new development opportunities

Architecture-Adaptive Uncertainty Fusion for Deepfake Detection

arXiv:2606.06666v1 Announce Type: new Abstract: Deepfake detection systems achieve near-perfect accuracy on benchmarks, yet forensic deployment demands reliable prediction uncertainty. Existing uncert

Are Large Language Models Suitable for Graph Computation? Progress and Prospects

arXiv:2606.06865v1 Announce Type: new Abstract: Large language models (LLMs) have been increasingly explored for graph computation, where tasks require reasoning over structured relationships and algo

researcharxiv-cs-cl

Bradley-Terry Rankings for Recommender Systems Across Dataset Taxonomies

arXiv:2606.07492v1 Announce Type: cross Abstract: The ranking of recommendation algorithms is a challenging problem since model performance is sensitive to dataset characteristics such as sparsity, se

Breaking the Ice: Analyzing Cold Start Latency in vLLM

arXiv:2606.07362v1 Announce Type: new Abstract: As scalable inference services become popular, the cold start latency of an inference engine becomes important. Today, vLLM has evolved into the de fact

Breaking the Tuning Barrier: Zero-Hyperparameters Yield Multi-Corner Analysis Via Learned Priors

arXiv:2603.13092v2 Announce Type: replace Abstract: Yield Multi-Corner Analysis validates circuits across 25+ Process-Voltage-Temperature corners, resulting in a combinatorial simulation cost of O(K i

Capturing non-Markovian dynamics in non-equilibrium stochastic systems using flow matching

arXiv:2606.06658v1 Announce Type: new Abstract: Hydrodynamic models of stochastic particle systems represented by coarse-grained stochastic partial differential equations (SPDE), such as the regulariz

CF-JEPA: Mask-free forward prediction with asymmetric encoder utilization for time-series representation learning

arXiv:2606.07031v1 Announce Type: new Abstract: Self-supervised learning (SSL) for time-series representation learning is dominated by two paradigms: contrastive methods, which face challenges in cons

Characterization of Gaussian Universality Breakdown in High-Dimensional Empirical Risk Minimization

arXiv:2604.03146v2 Announce Type: replace-cross Abstract: We study high-dimensional convex empirical risk minimization (ERM) under general non-Gaussian data designs. By heuristically extending the Con

Characterize Then Distill: Mechanistic Reasoning in Large Output Spaces

arXiv:2606.06840v1 Announce Type: cross Abstract: Modern reasoning models offer surprisingly strong zero-shot performance on challenging multi-label tasks that require selecting a small set of relevan

Applications

ChemQuests: A Curated Chemistry Question-Answer Database Extracted from ChemRxiv papers

arXiv:2505.05232v3 Announce Type: replace Abstract: The rapid expansion of chemistry literature poses significant challenges for researchers seeking to efficiently access domain-specific knowledge. To

applicationsarxiv-cs-ai

ChronoForest: Closed-Loop Multi-Tree Diffusion Planning for Efficient Bridge Search and Route Composition

arXiv:2606.06618v1 Announce Type: cross Abstract: How can we plan long-horizon routes that reach designated goals, visit required waypoints, and remain short when only short-horizon offline trajectori

CoMetaPNS: Continually Meta-learning Personalized Neural Surrogates for Cardiac Electrophysiology Simulations

arXiv:2606.07488v1 Announce Type: new Abstract: Personalized virtual heart simulations face challenges in model personalization and computational cost. While neural surrogates offer state-of-the-art s

Compliance-Based Sensor Placement for Force Sensing on a Sensorized Prostate Phantom

arXiv:2606.06977v1 Announce Type: new Abstract: This work presents a compliance-based sensor placement method for force sensing on a sensorized prostate phantom designed for Digital Rectal Examination

researcharxiv-cs-ro

COMPOSE: Hypergraph Cover Optimization for Multi-view 3D Human Pose Estimation

arXiv:2601.09698v2 Announce Type: replace Abstract: 3D human pose estimation from sparse multi-view camera rigs is an essential task for numerous applications, including action recognition, sports ana

Conformal Disentanglement and Latent-Space Curation: A Neural Framework for Perspective Synthesis, Differentiation and Targeted Generation

arXiv:2408.15344v2 Announce Type: replace Abstract: Many scientific and engineering problems involve observing a common phenomenon through multiple heterogeneous sensors or measurement modalities. Suc