Search: “applications”

Generative AI Purpose-built for Social and Mental Health: A Real-World Pilot

arXiv:2511.11689v4 Announce Type: replace-cross Abstract: Generative AI chatbots built for mental health could extend access to care, but evidence from real-world use is limited. We report a single-ar

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Applications

Ghost in the Encoder: Decodable Artist Identity Representations in Lyrics-to-Song Generation

DGX agent

arXiv:2609.39552v1 Announce Type: cross Abstract: Text-to-song generation models can be prompted to imitate specific artists or regurgitate entire songs from their training data. Although these phenom

applicationsarxiv-cs-lg

1 Oct 2026

Gromov-Wasserstein Distillation for Inductive Multi-View Embedding

arXiv:2609.40047v1 Announce Type: new Abstract: Gromov-Wasserstein multidimensional scaling (GW-MDS) learns low-dimensional representations from relational data but remains transductive, providing no

Local Ai

Grounding with Confidence: Controllable Generative Video Temporal Grounding

arXiv:2609.39883v1 Announce Type: new Abstract: Video temporal grounding supports applications such as video search, content review, and automated editing by localizing events described in natural lan

local-aiarxiv-cs-cv

HIGS: Hierarchical Implicit Grids for Joint Geometric and Semantic Scene Understanding

arXiv:2609.38620v1 Announce Type: new Abstract: Neural implicit representations have had a significant impact on scene reconstruction by enabling robots to build continuous, differentiable, and high-f

L1-MPPI: L1 Adaptive Model Predictive Path Integral for Agile UAV Control

arXiv:2609.38467v1 Announce Type: new Abstract: This work proposes the L1 Adaptive Model Predictive Path Integral (L1-MPPI). It cascades L1 adaptive control with the Model Predictive Path Integral (MP

Learning What to Forget: Distributional Unlearning for LLM Representation Spaces

arXiv:2609.38929v1 Announce Type: new Abstract: Machine learning systems increasingly face the need to remove the influence of entire data domains, such as toxic language, harmful behavior, or topical

LegalPincite: Multi-level Legal Information Retrieval Dataset

arXiv:2608.03756v2 Announce Type: cross Abstract: A common task in legal Information Retrieval (IR) is to find relevant legal sources from case-law collections. While legal practice often requires pin

LogiC-Diff: Embedding Security Properties Into AI-Enabled Cyber-Physical Systems

arXiv:2609.38381v1 Announce Type: cross Abstract: AI-enabled Cyber-Physical Systems (CPS) are highly vulnerable to adversarial and anomalous inputs, where small perturbations can induce cascading erro

Low-Discrepancy Dither for Quantized Recurrent State Caches

arXiv:2609.39185v1 Announce Type: new Abstract: Mamba-style and hybrid language models compress their past into a fixed-size recurrent state that is rewritten at every generated token. Storing this st

NEXUS: Perceptive Whole-Body Control for Terrain-Adaptive Teleoperation

arXiv:2609.39000v1 Announce Type: new Abstract: Whole-body teleoperation requires a humanoid robot to reproduce a human operator's behavior even when their terrains differ. This demands that the robot

Observability Analysis and Online Calibration of Visual-Inertial-Wheel Odometry for 4WIS4WID Mobile Robots

arXiv:2609.38462v1 Announce Type: new Abstract: In this paper, we present a visual-inertial-wheel odometry (VIWO) framework with online calibration for four-wheel independently steered and driven (4WI

PneuTac: Tactile Manipulation with Soft Pneumatic Robots via Unified MPM-Gaussian Splatting Simulation

arXiv:2609.38418v1 Announce Type: new Abstract: Soft robots and tactile sensors have demonstrated great potential in delicate manipulation tasks. Soft pneumatic robots enable safe contact through comp

Reasoning Externalization for Faithful Large Language Model Narratives of Stock Return Predictions

arXiv:2609.38869v1 Announce Type: new Abstract: In finance, interpreting machine learning predictions is essential, yet the numerical outputs of explainable AI can be difficult for non-experts to unde

Reconstructing the Dynamic World: A Representation-Centric View of 4D Scene Reconstruction

arXiv:2609.39960v1 Announce Type: new Abstract: 4D scene reconstruction aims to recover the evolving geometry, appearance, and motion of dynamic environments from visual observations. Despite substant

Rising Multi-Armed Bandits with Known Horizons

arXiv:2602.10727v3 Announce Type: replace Abstract: Rising Multi-Armed Bandits (RMABs) model sequential decision problems where each arm's expected reward improves with repeated pulls. In such problem

Robust Transfer Learning for Paper ECG Recognition

arXiv:2609.39581v1 Announce Type: cross Abstract: Paper ECG recognition is challenging because real-world ECG images vary in layout, physical artifacts, and label availability. We introduce RobECG-CL,

SOLAR: SVD-Optimized Lifelong Attention for Recommendation

arXiv:2603.02561v2 Announce Type: replace-cross Abstract: Attention mechanism remains the defining operator in Transformers since it provides expressive global credit assignment, yet its quadratic cos

Spatio-Temporal Partial Sensing Forecast for Long-term Traffic

arXiv:2408.02689v3 Announce Type: replace-cross Abstract: Traffic forecasting uses recent measurements by sensors installed at chosen locations to forecast the future road traffic. Existing work eithe

Research

StreamDecisionBench: Evaluating Decisions in Force on Evolving Language Streams

arXiv:2609.38612v1 Announce Type: new Abstract: As natural language drives more applications, language models increasingly run inside programs as decision components: the program sends them the curren

researcharxiv-cs-cl

TO-mdiSPAs: Topology Optimization of multi-directional Soft Pneumatic Actuators

arXiv:2609.39618v1 Announce Type: new Abstract: Soft pneumatic actuators (SPAs) are highly promising and have been extensively explored within the field of soft robotics. Under pneumatic pressure load

Towards Robust Time Series Learning via Capacity-Centric Modulation

arXiv:2609.39489v1 Announce Type: new Abstract: Sample-level reliability heterogeneity is common in deep time series learning. Standard training pipelines apply a uniform regularization setting to all

UBTree: Parallel Tree Drafting via Unigram and Bigram Models for Speculative Decoding

arXiv:2609.39972v1 Announce Type: new Abstract: Speculative decoding accelerates language model inference by verifying multiple draft tokens in a single target-model pass. Recent parallel drafters hav

A QCQP-Representable IMU Pre-Integration Factor for Certifiable State Estimation

arXiv:2609.38048v1 Announce Type: new Abstract: We propose a QCQP-representable IMU pre-integration factor that enables certifiable estimation with pre-integrated inertial measurements. To the best of

AdaST: Adaptive Coupling for Spatial-Temporal Forecasting

arXiv:2609.36119v1 Announce Type: new Abstract: Spatial-temporal (ST) forecasting underpins many real-world systems such as traffic, climate, and energy networks. While existing methods implicitly ass

Adversarial Defense in Cybersecurity: A Systematic Review of GANs for Threat Detection and Mitigation

arXiv:2509.20411v3 Announce Type: replace-cross Abstract: Machine learning-based cybersecurity systems are highly vulnerable to adversarial attacks, while Generative Adversarial Networks (GANs) act as

Research

An Effective, Reliable, and Robust Framework for Human Activity Recognition Using Wearable Sensors

arXiv:2609.36848v1 Announce Type: new Abstract: Human Activity Recognition (HAR) through wearable sensors greatly improves the quality of human life through its multiple applications. For HAR, multi-s

researcharxiv-cs-lg

APM-Bench: Benchmarking Cross-session Persistent Memory for Egocentric Streaming Video Assistants

arXiv:2609.37559v1 Announce Type: new Abstract: To serve as real-world personal assistants, streaming video models need persistent memory that retains past experiences for later use. Yet existing stre

Beyond Discrimination: Calibrated Geoprior Fusion for Bioacoustic Monitoring

arXiv:2609.35863v1 Announce Type: cross Abstract: Modern bioacoustic foundation models like Perch and BirdNET can identify species with high discriminative accuracy, yet their confidence scores are of

CIRCLE: A Framework for Evaluating AI from a Real-World Lens

arXiv:2602.24055v5 Announce Type: replace Abstract: This study proposes CIRCLE, a six-stage, lifecycle-based framework to bridge the reality gap between model-centric performance metrics and AI system

Cool the Sampler, Not the Learner: Sampling Temperature Moves the Staleness Cliff of Importance-Corrected GRPO

arXiv:2609.36953v1 Announce Type: cross Abstract: Production RL for language models lets the sampler fall behind the learner and repairs the resulting mismatch with a truncated importance weight. We a

Designing a Boundary Negotiating Artifact for Collaborative Socio-Technical Sense-Making in AI Regulatory Sandboxes

arXiv:2609.37109v1 Announce Type: cross Abstract: The rapid, unpredictable advancements in AI system capabilities has seen regulators take adaptive and experimental approaches to policymaking. Establi

DQ-MPCC: Dual-Quaternion MPCC for Quadrotor Racing

arXiv:2609.36482v1 Announce Type: new Abstract: Quadrotor racing demands aggressive attitude and progress control while passing through every gate, and conventional quadrotor MPCC formulations state t

DRHeC: Differentiable Rendering for Hand-Eye Calibration with RGB-Based Gradients

arXiv:2609.36779v1 Announce Type: cross Abstract: Accurate hand-eye calibration is crucial for precision manipulation. Traditional methods rely on markers, with their precision dependent on marker acc

EVO-WAM: Evolving World Action Models through Video-Action Verification

arXiv:2609.38057v1 Announce Type: new Abstract: Improving robot policies on new tasks without collecting additional expert demonstrations remains a central challenge in robot learning. World action mo

Foresight at the Event Boundary: Evaluating Physical Prediction in Video World Models

arXiv:2609.36531v1 Announce Type: new Abstract: Video world models are largely regarded as predictive models of the physical world and are therefore expected to anticipate the consequences of observed

Harnessing Large Language Models to Compile Task-Relevant Context into Bayesian Optimisation

arXiv:2609.36788v1 Announce Type: new Abstract: Incorporating rich task-relevant context, such as domain knowledge and external observations, is a key capability yet remains challenging for Bayesian o

How Much Prompt Is Enough? A Blackbox Minimization of Few-Shots in LLMs

arXiv:2609.36289v1 Announce Type: cross Abstract: Prompts are the primary mechanism for directing the behavior of large language models (LLMs). Yet the internal structure and causal hierarchy of promp

In-context Robot Learning Made Simple: A Democratized Recipe for Manipulation Tasks

arXiv:2609.38173v1 Announce Type: new Abstract: We study robotic in-context learning (ICL), an emerging paradigm that enables robots to infer and execute tasks from visual demonstrations. Despite its

Independent Verification Paths Are Not Independent: A Case Study of Common-Mode Failure in a Satellite Catalogue Pipeline

arXiv:2609.37603v1 Announce Type: cross Abstract: A common safeguard for a data pipeline is redundant computation: derive each published number by two routes built on different technology and refuse t

Model Releases

Koa-action: Fast and Consistent Structured Decision Making with Generative LLMs

model-releasesarxiv-cs-lg

arXiv:2609.36115v1 Announce Type: new Abstract: Industry applications often demand low-latency classification, yet current large language model (LLM) approaches remain poorly suited for latency-critic

LAURA: Knowledge Distillation for Interpretable Ambiguous Clause Identification in Legal Contracts

arXiv:2609.36707v1 Announce Type: new Abstract: Legal contracts contain ambiguities that expose enterprises to financial and legal risks. Some ambiguities allow flexible interpretation without trigger

Learning Continuous Patient Trajectories from Electronic Health Records

arXiv:2609.36144v1 Announce Type: new Abstract: Electronic health records provide irregular observations of latent patient states that evolve continuously over time. Recent autoregressive models condi

Learning from Shared-Control Overrides: Context-Driven Acceleration Profile Prediction for Personalized Overtaking

arXiv:2609.37684v1 Announce Type: new Abstract: Adaptive Cruise Control (ACC) systems are typically calibrated for an average driver, often resulting in a mismatch between vehicle behavior and individ

Learning to Recorrupt: Noise Distribution Agnostic Self-Supervised Image Denoising

arXiv:2603.25869v2 Announce Type: replace-cross Abstract: Self-supervised image denoising methods have traditionally relied on architectural constraints, pseudo-pair constructions, or specialized loss

Long-Term Memory-Guided Enhancement for Target Perception in Audio-Language Models

arXiv:2609.36577v1 Announce Type: cross Abstract: Audio large language models (ALLMs) can reason about the content of audio recordings to perform complex tasks. However, these capabilities usually col

Matrix-game 2.0: An open-source, real-time, and streaming interactive world model

arXiv:2508.13009v5 Announce Type: replace Abstract: Recent advances in interactive video generations have demonstrated diffusion model's potential as world models by capturing complex physical dynamic

MeteoVerse: Unified Weather-Controllable Video World Model

arXiv:2609.36810v1 Announce Type: new Abstract: Video world models aim to predict future content from an observed scene while following prescribed camera motion. Real-world scene evolution is determin