Search: “research”

Pyramid MoA: A Probabilistic Framework for Cost-Optimized Anytime Inference

arXiv:2602.19509v3 Announce Type: replace-cross Abstract: We observe that LLM cascading and routing implicitly solves an anytime computation problem -- a class of algorithms, well-studied in classical

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Quantifying Weighted Morphological Content of Large-Scale Structures via Simulation-Based Inference

DGX agent

arXiv:2511.03636v2 Announce Type: replace-cross Abstract: We perform a simulation-based forecasting analysis to compare the cosmological constraining power of higher-order summary statistics of the la

researcharxiv-cs-lg

14 Apr 2026

Query Lower Bounds for Diffusion Sampling

arXiv:2604.10857v1 Announce Type: cross Abstract: Diffusion models generate samples by iteratively querying learned score estimates. A rapidly growing literature focuses on accelerating sampling by mi

Quotation-Based Data Retention Mechanism for Data Privacy in LLM-Empowered Network Services

arXiv:2503.23001v5 Announce Type: replace Abstract: The deployment of large language models (LLMs) for next-generation network optimization introduces novel data governance challenges. mobile network

R2E-VID: Two-Stage Robust Routing via Temporal Gating for Elastic Edge-Cloud Video Inference

arXiv:2604.09681v1 Announce Type: cross Abstract: With the rapid growth of large-scale video analytics applications, edge-cloud collaborative systems have become the dominant paradigm for real-time in

RADA: Region-Aware Dual-encoder Auxiliary learning for Barely-supervised Medical Image Segmentation

arXiv:2604.11164v1 Announce Type: new Abstract: Deep learning has greatly advanced medical image segmentation, but its success relies heavily on fully supervised learning, which requires dense annotat

ReadMOF: Structure-Free Semantic Embeddings from Systematic MOF Nomenclature for Machine Learning

arXiv:2604.10568v1 Announce Type: new Abstract: Systematic chemical names, such as IUPAC-style nomenclature for metal-organic frameworks (MOFs), contain rich structural and compositional information i

Real-Time Human Reconstruction and Animation using Feed-Forward Gaussian Splatting

arXiv:2604.10259v1 Announce Type: new Abstract: We present a generalizable feed-forward Gaussian splatting framework for human 3D reconstruction and real-time animation that operates directly on multi

ReaLiTy and LADS: A Unified Framework and Dataset Suite for LiDAR Adaptation Across Sensors and Adverse Weather Conditions

arXiv:2604.10213v1 Announce Type: cross Abstract: Reliable LiDAR perception requires robustness across sensors, environments, and adverse weather. However, existing datasets rarely provide physically

Reason Only When Needed: Efficient Generative Reward Modeling via Model-Internal Uncertainty

arXiv:2604.10072v1 Announce Type: new Abstract: Recent advancements in the Generative Reward Model (GRM) have demonstrated its potential to enhance the reasoning abilities of LLMs through Chain-of-Tho

Reasoning as Data: Representation-Computation Unity and Its Implementation in a Domain-Algebraic Inference Engine

arXiv:2604.10908v1 Announce Type: new Abstract: Every existing knowledge system separates storage from computation. We show this separation is unnecessary and eliminate it. In a standard triple is_a(A

RECIPER: A Dual-View Retrieval Pipeline for Procedure-Oriented Materials Question Answering

arXiv:2604.11229v1 Announce Type: cross Abstract: Retrieving procedure-oriented evidence from materials science papers is difficult because key synthesis details are often scattered across long, conte

Reconciling distributed compliance with high-performance control in continuum soft robotics

arXiv:2603.16630v2 Announce Type: replace Abstract: High-performance closed-loop control of truly soft continuum manipulators has remained elusive. Experimental demonstrations have largely relied on s

researcharxiv-cs-ro

RedNote-Vibe: A Dataset for Capturing Temporal Dynamics of AI-Generated Text in Lifestyle Social Media

arXiv:2509.22055v2 Announce Type: replace Abstract: We introduce RedNote-Vibe, a dataset spanning five years (pre-LLM to July 2025) sourced from lifestyle platform RedNote (Xiaohongshu), capturing the

Replicable Composition

arXiv:2604.10423v1 Announce Type: new Abstract: Replicability requires that algorithmic conclusions remain consistent when rerun on independently drawn data. A central structural question is compositi

Representation-Aligned Multi-Scale Personalization for Federated Learning

arXiv:2604.11278v1 Announce Type: new Abstract: In federated learning (FL), accommodating clients with diverse resource constraints remains a significant challenge. A widely adopted approach is to use

Reproduction Beyond Benchmarks: ConstBERT and ColBERT-v2 Across Backends and Query Distributions

arXiv:2604.09982v1 Announce Type: cross Abstract: Reproducibility must validate architectural robustness, not just numerical accuracy. We evaluate ColBERT-v2 and ConstBERT across five dimensions, find

Resource Consumption Threats in Large Language Models

arXiv:2603.16068v3 Announce Type: replace-cross Abstract: Given limited and costly computational infrastructure, resource efficiency is a key requirement for large language models (LLMs). Efficient LL

Retrieval Is Not Enough: Why Organizational AI Needs Epistemic Infrastructure

arXiv:2604.11759v1 Announce Type: new Abstract: Organizational knowledge used by AI agents typically lacks epistemic structure: retrieval systems surface semantically relevant content without distingu

Riemannian Zeroth-Order Gradient Estimation with Structure-Preserving Metrics for Geodesically Incomplete Manifolds

arXiv:2601.08039v2 Announce Type: replace Abstract: In this paper, we study Riemannian zeroth-order optimization in settings where the underlying Riemannian metric g is geodesically incomplete, and th

rPPG-VQA: A Video Quality Assessment Framework for Unsupervised rPPG Training

arXiv:2604.11156v1 Announce Type: new Abstract: Unsupervised remote photoplethysmography (rPPG) promises to leverage unlabeled video data, but its potential is hindered by a critical challenge: traini

S^3: Structured Sparsity Specification

arXiv:2604.11315v1 Announce Type: cross Abstract: We introduce the Structured Sparsity Specification (S^3), an algebraic framework for defining, composing, and implementing structured sparse patterns.

S4M: 4-points to Segment Anything

arXiv:2503.05534v3 Announce Type: replace Abstract: Purpose: The Segment Anything Model (SAM) promises to ease the annotation bottleneck in medical segmentation, but overlapping anatomy and blurred bo

Sat2Sound: A Unified Framework for Zero-Shot Soundscape Mapping

arXiv:2505.13777v2 Announce Type: replace-cross Abstract: We present Sat2Sound, a unified multimodal framework for geospatial soundscape understanding, designed to predict and map the distribution of

Scaling Up AI-Generated Image Detection with Generator-Aware Prototypes

arXiv:2512.12982v2 Announce Type: replace Abstract: The pursuit of a universal AI-generated image (AIGI) detector often relies on aggregating data from numerous generators to improve generalization. H

ScoRe-Flow: Complete Distributional Control via Score-Based Reinforcement Learning for Flow Matching

arXiv:2604.10962v1 Announce Type: new Abstract: Flow Matching (FM) policies have emerged as an efficient backbone for robotic control, offering fast and expressive action generation that underpins rec

researcharxiv-cs-ro

Self-Calibrating Language Models via Test-Time Discriminative Distillation

arXiv:2604.09624v1 Announce Type: new Abstract: Large language models (LLMs) are systematically overconfident: they routinely express high certainty on questions they often answer incorrectly. Existin

Self-Correcting RAG: Enhancing Faithfulness via MMKP Context Selection and NLI-Guided MCTS

arXiv:2604.10734v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) substantially extends the knowledge boundary of large language models. However, it still faces two major challenges

Semantic-Space Exploration and Exploitation in RLVR for LLM Reasoning

arXiv:2509.23808v4 Announce Type: replace-cross Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) for LLM reasoning is often framed as balancing exploration and exploitation in action sp

SemEnrich: Self-Supervised Semantic Enrichment of Radiology Reports for Vision-Language Learning

arXiv:2604.09887v1 Announce Type: new Abstract: Medical vision-language datasets are often limited in size and biased toward negative findings, as clinicians report abnormalities mostly but might omit

Sharpness-Aware Surrogate Training for On-Sensor Spiking Neural Networks

arXiv:2604.09696v1 Announce Type: cross Abstract: Spiking neural networks (SNNs) are a natural computational model for on-sensor and near-sensor vision, where event driven processors must operate unde

Should We be Pedantic About Reasoning Errors in Machine Translation?

arXiv:2604.09890v1 Announce Type: cross Abstract: Across multiple language pairings (English o {Spanish, French, German, Mandarin, Japanese, Urdu, Cantonese}), we find reasoning errors in translation.

SIGMA: An Efficient Heterophilous Graph Neural Network with Fast Global Aggregation

arXiv:2305.09958v5 Announce Type: replace Abstract: Graph neural networks (GNNs) realize great success in graph learning but suffer from performance loss when meeting heterophily, i.e. neighboring nod

SinkTrack: Attention Sink based Context Anchoring for Large Language Models

arXiv:2604.10027v1 Announce Type: new Abstract: Large language models (LLMs) suffer from hallucination and context forgetting. Prior studies suggest that attention drift is a primary cause of these pr

Slithering Through Gaps: Capturing Discrete Isolated Modes via Logistic Bridging

arXiv:2604.10821v1 Announce Type: new Abstract: High-dimensional and complex discrete distributions often exhibit multimodal behavior due to inherent discontinuities, posing significant challenges for

Soft Graph Transformer for MIMO Detection

arXiv:2509.12694v5 Announce Type: replace Abstract: We propose the Soft Graph Transformer (SGT), a soft-input-soft-output neural architecture designed for MIMO detection. While Maximum Likelihood (ML)

Solver-Independent Automated Problem Formulation via LLMs for High-Cost Simulation-Driven Design

arXiv:2512.18682v2 Announce Type: replace Abstract: In the high-cost simulation-driven design domain, translating ambiguous design requirements into a mathematical optimization formulation is a bottle

Solving and learning advective multiscale Darcian dynamics with the Neural Basis Method

arXiv:2602.17776v2 Announce Type: replace-cross Abstract: Physics-governed models are increasingly paired with machine learning for accelerated predictions, yet most 'physics--informed' formulations t

Sparse Hypergraph-Enhanced Frame-Event Object Detection with Fine-Grained MoE

arXiv:2604.11140v1 Announce Type: new Abstract: Integrating frame-based RGB cameras with event streams offers a promising solution for robust object detection under challenging dynamic conditions. How

Spectral Kernel Dynamics via Maximum Caliber: Fixed Points, Geodesics, and Phase Transitions

arXiv:2604.09745v1 Announce Type: cross Abstract: We derive a closed-form geometric functional for kernel dynamics on finite graphs by applying the Maximum Caliber (MaxCal) variational principle to th

SpectralLoRA: Is Low-Frequency Structure Sufficient for LoRA Adaptation? A Spectral Analysis of Weight Updates

arXiv:2604.10649v1 Announce Type: cross Abstract: We present a systematic empirical study of the spectral structure of LoRA weight updates. Through 2D Discrete Cosine Transform (DCT) analysis of train

SpeechLess: Micro-utterance with Personalized Spatial Memory-aware Assistant in Everyday Augmented Reality

arXiv:2602.00793v2 Announce Type: replace-cross Abstract: Speaking aloud to a wearable AR assistant in public can be socially awkward, and re-articulating the same requests every day creates unnecessa

Stability of a Generalized Debiased Lasso with Applications to Resampling-Based Variable Selection

arXiv:2405.03063v2 Announce Type: replace-cross Abstract: We propose a generalized debiased Lasso estimator based on a stability principle. When a single column of the design matrix is perturbed, the

StableToken: A Noise-Robust Semantic Speech Tokenizer for Resilient SpeechLLMs

arXiv:2509.22220v2 Announce Type: replace Abstract: Prevalent semantic speech tokenizers, designed to capture linguistic content, are surprisingly fragile. We find they are not robust to meaning-irrel

STGV: Spatio-Temporal Hash Encoding for Gaussian-based Video Representation

arXiv:2604.10910v1 Announce Type: new Abstract: 2D Gaussian Splatting (2DGS) has recently become a promising paradigm for high-quality video representation. However, existing methods employ content-ag

StreetDesignAI: A Multi-Persona Evaluation System for Inclusive Infrastructure Design

arXiv:2601.15671v2 Announce Type: replace-cross Abstract: Designing cycling infrastructure requires balancing the competing needs of diverse user groups, yet designers often struggle to anticipate how

STS-Mixer: Spatio-Temporal-Spectral Mixer for 4D Point Cloud Video Understanding

arXiv:2604.11637v1 Announce Type: new Abstract: 4D point cloud videos capture rich spatial and temporal dynamics of scenes which possess unique values in various 4D understanding tasks. However, most

STU-PID: Steering Token Usage via PID Controller for Efficient Large Language Model Reasoning

arXiv:2506.18831v2 Announce Type: replace Abstract: Large Language Models employing extended chain-of-thought (CoT) reasoning often suffer from the overthinking phenomenon, generating excessive and re