Search: “models”

MimicLM: Zero-Shot Voice Imitation through Autoregressive Modeling of Pseudo-Parallel Speech Corpora

arXiv:2604.11552v1 Announce Type: cross Abstract: Voice imitation aims to transform source speech to match a reference speaker's timbre and speaking style while preserving linguistic content. A straig

safetyarxiv-cs-cl

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Research

Modeling, Analysis and Activation of Planar Viscoelastically-combined Rimless Wheels

DGX agent

arXiv:2604.11295v1 Announce Type: new Abstract: This paper proposes novel passive-dynamic walkers formed by two cross-shaped frames and eight viscoelastic elements. Since it is a combination of two fo

researcharxiv-cs-ro

14 Apr 2026

MSA: Memory Sparse Attention for Efficient End-to-End Memory Model Scaling to 100M Tokens

arXiv:2603.23516v2 Announce Type: replace-cross Abstract: Long-term memory is a cornerstone of human intelligence. Enabling AI to process lifetime-scale information remains a long-standing pursuit in

agentsarxiv-cs-ai

MSTN: A Lightweight and Fast Model for General TimeSeries Analysis

arXiv:2511.20577v3 Announce Type: replace Abstract: Real-world time series often exhibit strong non-stationarity, complex nonlinear dynamics, and behavior expressed across multiple temporal scales, fr

local-aiarxiv-cs-lg

UBio-MolFM: A Universal Molecular Foundation Model for Bio-Systems

arXiv:2602.17709v2 Announce Type: replace-cross Abstract: All-atom molecular simulation serves as a quintessential ``computational microscope'' for understanding the machinery of life, yet it remains

local-aiarxiv-cs-ai

UHD-GPGNet: UHD Video Denoising via Gaussian-Process-Guided Local Spatio-Temporal Modeling

arXiv:2604.11014v1 Announce Type: new Abstract: Ultra-high-definition (UHD) video denoising requires simultaneously suppressing complex spatio-temporal degradations, preserving fine textures and chrom

local-aiarxiv-cs-cv

Commanding Humanoid by Free-form Language: A Large Language Action Model with Unified Motion Vocabulary

arXiv:2511.22963v2 Announce Type: replace-cross Abstract: Enabling humanoid robots to follow free-form language commands is critical for seamless human-robot interaction, collaborative task execution,

13 Apr 2026

Dual Mamba for Node-Specific Representation Learning: Tackling Over-Smoothing with Selective State Space Modeling

arXiv:2511.06756v3 Announce Type: replace Abstract: Over-smoothing remains a fundamental challenge in deep Graph Neural Networks (GNNs), where repeated message passing causes node representations to b

researcharxiv-cs-lg

13 Apr 2026

Hardware

Fast Model-guided Instance-wise Adaptation Framework for Real-world Pansharpening with Fidelity Constraints

arXiv:2604.08903v1 Announce Type: new Abstract: Pansharpening aims to generate high-resolution multispectral (HRMS) images by fusing low-resolution multispectral (LRMS) and high-resolution panchromati

hardwarearxiv-cs-cv

13 Apr 2026

Development of ML model for triboelectric nanogenerator based sign language detection system

arXiv:2604.06220v1 Announce Type: cross Abstract: Sign language recognition (SLR) is vital for bridging communication gaps between deaf and hearing communities. Vision-based approaches suffer from occ

researcharxiv-cs-ai

FBS: Modeling Native Parallel Reading inside a Transformer

arXiv:2601.21708v2 Announce Type: replace Abstract: Large language models (LLMs) excel across many tasks, yet inference is still dominated by strictly token-by-token autoregression. Existing accelerat

researcharxiv-cs-ai

Toward Personalized Darts Training: A Data-Driven Framework Based on Skeleton-Based Biomechanical Analysis and Motion Modeling

arXiv:2604.01130v3 Announce Type: replace Abstract: As sports training becomes more data-driven, traditional dart coaching based mainly on experience and visual observation is increasingly inadequate

local-aiarxiv-cs-lg

Towards Privacy-Preserving Large Language Model: Text-free Inference Through Alignment and Adaptation

arXiv:2604.06831v1 Announce Type: cross Abstract: Current LLM-based services typically require users to submit raw text regardless of its sensitivity. While intuitive, such practice introduces substan

Amortizing Sequential Experimental Design in Reasoning LLMs

arXiv:2610.20832v1 Announce Type: cross Abstract: Despite their extensive pretraining knowledge and strong reasoning capabilities, large language models (LLMs) struggle to adaptively gather informatio

BiShield-TEE: On the (In-)Security of Unilateral Weight Obfuscation in On-Device TEE-Shielded LLM Partition

arXiv:2610.21565v1 Announce Type: cross Abstract: On-device deployment of large language models (LLMs) is increasingly adopted due to latency and privacy requirements, but exposes proprietary models t

CleanRM: Reward Modeling from Noisy Feedback with a Few Clean Feedback for RLHF

arXiv:2610.21138v1 Announce Type: new Abstract: Feedback noise is pervasive in preference data, arising from subjective human judgments, annotation mistakes, and imperfect LLM judges. Standard reward

CogDrift-4D: Hierarchical Multimodal Modeling of Temporal Behavioral Decay for MCI Detection

arXiv:2610.20877v1 Announce Type: cross Abstract: Early detection of mild cognitive impairment remains a critical bottleneck in dementia care, demanding scalable tools capable of capturing subtle beha

local-aiarxiv-cs-cl

EMO: A Closed-Loop Test-Time Computation Framework via Alternating Context Optimization and Logits Steering

arXiv:2610.22160v1 Announce Type: cross Abstract: Test-time context optimization adapts frozen language models through textual feedback, but ordinary conditional generation provides no separate contro

Evaluation Awareness Beyond English: Do LLMs Act Differently When Tested in Indic Languages?

arXiv:2610.22333v1 Announce Type: new Abstract: Large language models (LLMs) can often tell when they are being tested. This ability, known as evaluation awareness, can lead models to act more cautiou

From Perception to Prediction and Intervention: Benchmarking Proactive Video Assistants in Real-Life Scenarios

model-releasesarxiv-cs-lg

arXiv:2610.21568v1 Announce Type: new Abstract: Recent multimodal large language models have advanced video understanding, but existing benchmarks mainly evaluate whether models can interpret observed

Hy-Memory-30B-A3B: Attributed Reinforcement Learning for Long-Term Memory Writing

arXiv:2610.22196v1 Announce Type: new Abstract: External-memory systems extend language-model applications beyond a context window, but their quality depends critically on the model executing the writ

IKMo: Image-Keyframed Motion Generation with Trajectory-Pose Conditioned Motion Diffusion Model

arXiv:2505.21146v2 Announce Type: replace-cross Abstract: While text-to-motion generation is mainstream, integrating explicit spatial constraints has become a standard solution for precise animation.

local-aiarxiv-cs-cv

Learning from Interaction Experience via Localized Context Distillation

arXiv:2610.21427v1 Announce Type: new Abstract: Learning from interaction experience is essential for enabling large language models to continually improve during deployment. Context distillation offe

Mind the Delay: Latency-aware Query Routing for Heterogeneous LLM pools

arXiv:2607.18253v2 Announce Type: replace Abstract: Large language model (LLM) query routers typically assign each query to a suitable model that balances response accuracy and monetary cost. Subseque

researcharxiv-cs-ai

Momentum, Commentary Tone, and Earnings Surprise in LLM Financial Forecasts

arXiv:2610.22043v1 Announce Type: cross Abstract: Which inputs drive a language model's financial forecast? We construct synthetic earnings announcements that independently reverse 20-day momentum, no

MR-MPCC: Model Predictive Contouring Control for Robotic Manipulator Tracking under Moving Reference Frames

arXiv:2610.21292v1 Announce Type: new Abstract: Maintaining small path-tracking errors under moving reference frames is essential for robotic manipulation tasks with tight execution tolerances, such a

safetyarxiv-cs-ro

Perception or Reasoning? Diagnosing and Tackling Reinforcement Learning Bottlenecks in VLMs

model-releasesarxiv-cs-cv

arXiv:2610.21380v1 Announce Type: new Abstract: Reinforcement learning has brought strong gains to language model reasoning, but its improvements on visual tasks remain less consistent. One difficulty

SciPivot: Benchmarking Principal-Investigator Judgment at Pivotal Moments of Scientific AutoResearch Agents

arXiv:2610.21082v1 Announce Type: new Abstract: Large language model (LLM) agents can keep scientific experiments running for months with little human supervision, but reliable autonomous research als

Seeing is Believing: Benchmarking and Mitigating the Interference of Language Priors on Visual Perception in MLLMs

model-releasesarxiv-cs-cv

arXiv:2610.21902v1 Announce Type: new Abstract: Language priors in MLLMs can override visual evidence, impairing visual perception. Existing benchmarks assume shared priors across models and rely sole

Applications

Self-Refining Vision Language Model for Robotic Failure Detection and Reasoning

arXiv:2602.12405v2 Announce Type: replace-cross Abstract: Reasoning about failures is crucial for building reliable and trustworthy robotic systems. Prior approaches either treat failure reasoning as

applicationsarxiv-cs-lg

TEM: Temporal State Tracking Memory for Large Language Model Agents

arXiv:2610.21900v1 Announce Type: new Abstract: An agent's memory must remain useful as information changes across conversations. A new fact may replace an earlier value without making that value irre

agentsarxiv-cs-cl

A VR Training System for Robot-Assisted Vascular Intervention with Dual-Mode Control and Model-Based Interaction Response

arXiv:2610.19413v1 Announce Type: new Abstract: Virtual reality training for robot-assisted vascular intervention requires accurate robotic control and effective feedback on guidewire--vessel interact

researcharxiv-cs-ro

Alignment Faking - the Train -> Deploy Asymmetry: Through a Game-Theoretic Lens with Bayesian-Stackelberg Equilibria

arXiv:2511.17937v2 Announce Type: replace Abstract: Alignment faking is a form of strategic deception in AI in which models selectively comply with training objectives when they infer that they are in

AutoMARS: Automatic and Scalable Multi-Agent Large Language Model Framework for Supply Chain Risk Assessment

arXiv:2610.17206v1 Announce Type: new Abstract: We propose AutoMARS (Automatic Multi-Agent Risk Assessment), an agentic framework for automatic and scalable comparative risk assessment in supply chain

agentsarxiv-cs-ai

AutoSec-RAN: Specification-Grounded LLM Fine-Tuning for Automated Security Analysis of O-RAN

arXiv:2610.15995v1 Announce Type: cross Abstract: This paper presents AutoSec-RAN, a specification-grounded large language model (LLM) framework for automated security triage of Open Radio Access Netw

Beyond Benchmark Accuracy: A Diagnostic Test for LLM Chemical Prediction

arXiv:2610.19906v1 Announce Type: new Abstract: LLMs have achieved strong performance on chemical prediction benchmarks. However, existing evaluation methods typically provide target entity identity i

Applications

Contact-UAN: Unsupervised Actuator Networks as a Residual World Model for Humanoid Control

arXiv:2610.18991v1 Announce Type: new Abstract: Humanoid policies trained in simulation can transfer qualitatively to hardware while failing to transfer the force interactions learned during training,

applicationsarxiv-cs-ro

FACT: A Multimodal Force-Action-Track Foundation Model for Human-to-Robot Dexterity

arXiv:2610.19155v1 Announce Type: new Abstract: Human demonstrations offer a scalable alternative to costly robot data collection for dexterous manipulation, but most human datasets lack force measure

agentsarxiv-cs-ro

Following the Flow the Law Requires: Training Voice Agents to Transfer to Unseen Regulated Procedures in Debt Collection

arXiv:2610.18881v1 Announce Type: new Abstract: Voice agents built on large language models (LLMs) now handle customer calls, but in regulated applications completing the task is not enough: the agent

GateSight: Recurrent Memory Anticipates Attention Memory for Query-Agnostic KV Eviction in Hybrid LLMs

arXiv:2610.14754v1 Announce Type: new Abstract: Hybrid language models interleave Gated DeltaNet (GDN) layers, whose recurrent memory has a fixed size, with full-attention layers, whose key-value (KV)

How Well Do LLMs Perform in Peer Review? Evidence from Finance and Accounting

arXiv:2610.18435v1 Announce Type: cross Abstract: Referees increasingly use large language models (LLMs), while finance and accounting journals disagree about whether to allow it. We ask which part of

Language Steering for Multilingual In-Context Learning

arXiv:2602.02326v3 Announce Type: replace Abstract: If multilingual language model representations contain separable language-associated structure, then shifting between languages may require only sim

Hardware

Learning in Orbit: Onboard Training and Closed-Loop Attitude Control with a Thermal Segmentation Model on a Spacecraft

arXiv:2610.19122v1 Announce Type: new Abstract: Deep space missions increasingly require spacecraft capable of autonomously operating in environments with communication delays and bandwidth limitation

hardwarearxiv-cs-ro

Physics-Guided Multi-Fidelity Surrogate Modeling for Natural Supercavity Geometry of an Axisymmetric Conical Cavitator

arXiv:2610.18886v1 Announce Type: cross Abstract: Natural supercavitation behind conical cavitators generates a vapor-filled envelope that, when sustained over the full body of a high-speed underwater

researcharxiv-cs-lg

Reliable Text-to-SQL in Resource-Constrained Settings with Small LLMs via Iterative Retry Workflows

arXiv:2610.17305v1 Announce Type: new Abstract: Large Language Models (LLMs) have recently improved Text-to-SQL generation, but their computational cost can hinder deployment in resource-constrained s

Tutorials

ROI-Reasoning: Rational Optimization for Inference via Pre-Computation Meta-Cognition

arXiv:2601.03822v2 Announce Type: replace Abstract: Large language models (LLMs) can achieve strong reasoning performance with sufficient computation, but they do not inherently know how much computat

tutorialsarxiv-cs-ai

Scaling Multilingual Mixture-of-Experts: How Language Coverage Changes Capacity and Compute Allocation

arXiv:2610.20247v1 Announce Type: new Abstract: Multilingual models share capacity across languages, so adding languages can hurt performance on existing ones. Mixture-of-experts models expand this ca

researcharxiv-cs-cl

The Sharp Directions Are Against You: Curvature Analysis of Activation Steering

arXiv:2610.16084v1 Announce Type: new Abstract: Activation steering adds a vector to a language model's internal representations at inference time. It is a lightweight alternative to fine-tuning for b