Search: “research”

iLTM: Integrated Large Tabular Model

arXiv:2511.15941v2 Announce Type: replace-cross Abstract: Tabular data underpins decisions across science, industry, and public services. Despite rapid progress, advances in deep learning have not ful

Imaginative Generative AI: Crossing the Entropy Wall into Worlds Beyond Imitation

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arXiv:2608.09385v1 Announce Type: cross Abstract: Generative AI models are primarily designed to imitate the data distribution, an objective that neither corrects diversity lost by a learned generator

researcharxiv-cs-ai

11 Aug 2026

In-Context Density Estimation for Tabular Data

arXiv:2608.09348v1 Announce Type: new Abstract: Density estimation underlies many unsupervised tasks on tabular data such as anomaly detection, out-of-distribution detection, and data augmentation. Al

Inductive Graph Layout with Implicit Neural Fields

arXiv:2608.08876v1 Announce Type: cross Abstract: A graph layout is normally a table of N free coordinates. We optimise a function with a fixed number of parameters instead. This gives a drawing a sam

Information Routing across Batch Boundaries: Memory--Batch Tradeoffs in Lipschitz Bandits

arXiv:2608.07922v1 Announce Type: new Abstract: Adaptive learning needs both a state that preserves what observations imply and opportunities to act on that state. We study this width--depth tradeoff

Innovating with Generative AI: A Human Bottleneck Framework

arXiv:2608.07504v1 Announce Type: cross Abstract: We propose a human bottleneck perspective for understanding how generative AI transforms the innovation process. The central premise is that many cons

Integrating spectral and morphological plant features with decision-tree models for early-season cotton biomass and nitrogen status estimation from multi-year UAV data

arXiv:2608.07801v1 Announce Type: cross Abstract: Precision nitrogen (N) management (PNM) for cotton requires in-season monitoring of crop growth parameters and N status indicators to decide fertilize

Intelligence Foundation Model: A New Perspective to Approach Artificial General Intelligence

arXiv:2511.10119v4 Announce Type: replace Abstract: We propose a new perspective for approaching artificial general intelligence (AGI) through an intelligence foundation model (IFM). Unlike existing f

Intuitive Hand Positional Guidance Using McKibben-Based Surface Tactile Sensations to Shoulder and Elbow

arXiv:2608.09167v1 Announce Type: cross Abstract: Hand positional guidance with intuitive perception is crucial for enhancing user interaction and task performance in immersive environments. However,

researcharxiv-cs-ro

IRPol-Fuse: Energy-structure coordination for infrared polarization fusion under low visibility

arXiv:2608.07848v1 Announce Type: new Abstract: Robust perception under low-visibility conditions requires fused imagery that jointly preserves infrared thermal saliency and polarization-derived struc

Janus: An Algorithm-Evaluator Co-Evolution Framework for LLM-Driven Discovery under Expensive Evaluation Budgets

arXiv:2608.08189v1 Announce Type: new Abstract: LLM-driven program discovery relies on rapid evaluator feedback, but many scientific and engineering tasks require high-fidelity simulations, hardware e

JSGS: JPEG State-Guided Supervision for 3D Gaussian Splatting from Mixed-Quality Views

arXiv:2608.08659v1 Announce Type: new Abstract: Standard 3D Gaussian Splatting (3DGS) assumes that every input image faithfully samples scene radiance. However, mixed-quality JPEG images violate this

Latent-Frequency Validity: Fast Spectral Editing with Screened Video-VAE Transfer Operators

arXiv:2608.07569v1 Announce Type: cross Abstract: Direct spectral editing in video-VAE latents can control noise, flicker, smoothness, and frequency content without a decode--filter--reencode pass. Ho

LAUDE: LLM-Assisted Unit Test Generation and Debugging of Hardware DEsigns

arXiv:2601.08856v3 Announce Type: replace-cross Abstract: Unit tests are critical in the hardware design lifecycle to ensure that component design modules are functionally correct and conform to the s

Layerwise goal-oriented adaptivity for neural ODEs: an optimal control perspective

arXiv:2601.07397v2 Announce Type: replace-cross Abstract: In this work, we propose a novel layerwise adaptive construction method for neural network architectures. Our approach is based on a goal--ori

Learning Physical Interaction: A Survey of Tactile- and Force-aware Robot Learning

arXiv:2608.07558v1 Announce Type: cross Abstract: Physically grounded robot intelligence requires robots to perceive, reason about, and regulate their interactions with the physical world. This capabi

LHSDet: High-Resolution AI-Generated Image Detection via Visual Question Answering

arXiv:2608.07863v1 Announce Type: new Abstract: Driven by advances in diffusion models and autoregressive models, the fidelity and resolution of AI-generated images now rival those of real images. How

LibraSpec: Dynamic Diffusion-Based Speculative Decoding via Marginal-Gain-Driven Optimization

arXiv:2608.08721v1 Announce Type: cross Abstract: Speculative decoding accelerates large language model inference by drafting multiple tokens for parallel verification, with efficiency critically dete

LightAIR: Lightweight Action Inversion and Riemannian Rectification for Text-based Person Anomaly Search

arXiv:2608.09152v1 Announce Type: new Abstract: Traditional Text-based Person Search (TPS) is typically limited to matching static appearance attributes, severely neglecting dynamic action information

Linearized 2-Simplicial Attention

arXiv:2608.09307v1 Announce Type: new Abstract: We present a linearized form of 2-simplicial attention by rewriting the trilinear score as an inner product between a composite query and a key, so that

LITEWAY: LIghtweight HAR via Temporal Efficient highWAY

arXiv:2608.09421v1 Announce Type: cross Abstract: Wearable human activity recognition (HAR) remains challenging due to the computational and energy constraints of deep learning models on resource-limi

LLM-Based Embeddings for Program Analysis and Optimization

arXiv:2608.07894v1 Announce Type: new Abstract: Recent advances have highlighted the potential of machine learning, particularly Large Language Models (LLMs), for analyzing and optimizing programs. We

Logarithmic-Free Moment and Generalization Bounds for Uniformly Stable Algorithms

arXiv:2608.09870v1 Announce Type: cross Abstract: Uniform stability is a classical tool for controlling the generalization error of a learning algorithm. Bousquet, Klochkov, and Zhivotovskiy (2020) sh

LookAgain: Closed-Loop GUI Grounding with Visually Grounded Reflection

arXiv:2608.09723v1 Announce Type: new Abstract: Recent graphical user interface (GUI) grounders have significantly advanced single-shot accuracy on standard benchmarks, yet their performance degrades

LookME: Lookup-Based Multimodal Embeddings for Layer Injection in Vision-Language Models

arXiv:2607.16305v2 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) have achieved strong progress in multimodal understanding. However, scaling dense or sparse Mixture-of-Experts (

LoRA-based Adaptation Alone Is Not Enough: Understanding the Limits of Foundation Models for Face Presentation Attack Detection

arXiv:2608.09633v1 Announce Type: new Abstract: Face presentation attack detection (PAD) aims to reliably detect a wide range of presentation attacks. While PAD methods achieve strong performance with

Loss-Resilient Wireless Video Token Communication over Block Fading Channels

arXiv:2608.08698v1 Announce Type: new Abstract: Video token communication represents video content as discrete tokens that differ in their importance to reconstruction and exhibit temporal dependencie

Lying mirror using structured surfaces

arXiv:2410.15521v2 Announce Type: replace-cross Abstract: We introduce an all-optical system, termed the 'lying mirror', to hide input information by transforming it into misleading, ordinary-looking

'Many Are My Names': The Anatomy of the Assistant and Its Personas via Sparse Autoencoders

arXiv:2608.07852v1 Announce Type: new Abstract: How a language model internally represents who is speaking, the Assistant, an assigned roleplay persona, or a narrated story character, remains underexp

researcharxiv-cs-cl

Matrix Completion via Nonsmooth Regularization of Fully Connected Neural Networks

arXiv:2403.10232v2 Announce Type: replace-cross Abstract: Conventional matrix completion methods approximate the missing values by assuming the matrix to be low-rank, which leads to a linear approxima

Measuring and Reducing WebGPU Dispatch Overhead for LLM Inference

arXiv:2608.08730v1 Announce Type: new Abstract: Large Language Models are deployed to multiple types of environments, from internet browsers to edge devices, and WebGPU serves as a modern cross-platfo

Med-CRAFT: An Information System for Explainable and Configurable Construction of Multimodal Medical QA Datasets

arXiv:2512.01045v2 Announce Type: replace Abstract: Data-intensive artificial intelligence applications increasingly rely on large-scale, high-quality, explainable, and reproducible datasets, yet the

Mitigating Over-Personalization in LLMs via Structured Memory

arXiv:2608.08300v1 Announce Type: new Abstract: Conversational assistants increasingly rely on persistent long-term memory to personalize responses across sessions. However, when stored user informati

ML-PWS: Estimating the Mutual Information Between Experimental Time Series Using Neural Networks

arXiv:2508.16509v3 Announce Type: replace-cross Abstract: The ability to quantify information transmission is crucial for the analysis and design of both natural and engineered systems. For systems dr

MoE-Prism: Disentangling Monolithic Experts for Elastic MoE Services via Model-System Co-Designs

arXiv:2510.19366v2 Announce Type: replace Abstract: Mixture-of-Experts (MoE) scales model capacity through sparse activation, and is becoming an important architecture for large language models (LLMs)

researcharxiv-cs-cl

MoNo: Multiscale Optimal Transport Neural Operator for Solving PDEs on General Geometries

arXiv:2608.09764v1 Announce Type: cross Abstract: Transformer-based neural operators have achieved substantial progress in solving Partial Differential Equations (PDEs) by projecting spatial observati

Monotonicity-Guided Bottom-Up Petri Net Discovery: The SPECpp Framework

arXiv:2608.09398v1 Announce Type: cross Abstract: Process discovery is one of the central challenges in process mining. Petri nets are particularly attractive because simple local constructs can expre

MPPI Planning with Gaussian Based Human Cost Function for Social Navigation

arXiv:2608.08323v1 Announce Type: new Abstract: Safe robot navigation in crowded spaces requires planning that accounts for where people will be, not only where they are now. Model Predictive Path Int

researcharxiv-cs-ro

MRI super-resolution in ten sampling steps using a diffusion bridge model

arXiv:2608.08819v1 Announce Type: new Abstract: Objective. MRI provides excellent soft-tissue contrast, but long acquisition times can cause patient discomfort and lead to motion artifacts, forcing a

Multi-kernel spectral clustering: Entrywise eigenvector perturbation bounds and exact recovery

arXiv:2608.08704v1 Announce Type: cross Abstract: Kernel spectral clustering with a single bandwidth can be inadequate for data exhibiting multiple characteristic pairwise-distance scales, a problem p

Multilingual Emotion Neurons in Large Audio-Language Models

arXiv:2608.08772v1 Announce Type: new Abstract: Emotion is central to human communication, and its expression varies across languages. Large audio-language models (LALMs) achieve strong performance on

researcharxiv-cs-cl

Multimodal Skin Lesion Classification with Swin Transformer and Clinical Metadata Fusion

arXiv:2608.07574v1 Announce Type: new Abstract: Skin lesion classification plays an important role in supporting the early diagnosis of skin cancer. However, automated analysis remains challenging due

MusicLayout: Explicit Structural Planning for Controllable Text-to-Music Generation

arXiv:2608.09035v1 Announce Type: cross Abstract: Text-to-music generation has advanced rapidly, but current systems still rely primarily on global text prompts, leaving the structural organization of

MVMD: A Multi-View Approach for Enhanced Mirror Detection

arXiv:2608.07559v1 Announce Type: new Abstract: In 3D reconstruction, mirrors introduce significant challenges by creating distorted and fragmented spaces, resulting in inaccurate and unreliable 3D mo

NeuPAT: Neuron-aware Plasticity Allocation Tuning for Language-Preserving MLLMs

arXiv:2608.08107v1 Announce Type: cross Abstract: Multimodal expansion of large language models (LLMs) enables new perceptual capabilities but often compromises the language intelligence acquired duri

NeuralDMD: Interpretable Neural Representation of Dynamics from Sparse and Noisy Measurements

arXiv:2507.03094v2 Announce Type: replace Abstract: Many challenges in scientific imaging involve solving ill-posed inverse problems, where the goal is to recover spatio-temporal fields from indirect,

neuralGAM: An R Package for Fitting Generalized Additive Neural Networks

arXiv:2505.08610v2 Announce Type: replace-cross Abstract: Nowadays, Neural Networks are considered one of the most effective methods for various tasks such as anomaly detection, computer-aided disease

NewtonGS: Physics-Structured Object-Level Neural Newtonian Dynamics for Gaussian Scene Animation

arXiv:2608.07598v1 Announce Type: new Abstract: Animating objects in a static 3D Gaussian scene requires an explicit object-level dynamic state and a controllable model of object motion. Existing dyna