Search: “applications”

Learning efficient representations of complex constraints for scalable optimization

arXiv:2603.08283v2 Announce Type: replace Abstract: Complex constraints often make real-world optimization computationally prohibitive at the scale and speed required for operational decision-making.

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Applications

LSREP: A Longitudinal State-Replay Protocol for Evaluating Conversational Memory, with ICE v2 as an Audited Local-First Architecture

DGX agent

arXiv:2609.16730v1 Announce Type: new Abstract: Conversational memory changes during use, so endpoint question answering alone cannot establish how a persistent state accumulates, ages, or incorporate

applicationsarxiv-cs-ai

16 Sept 2026

Modality-Autoregressive World-Action Models

arXiv:2609.17524v1 Announce Type: new Abstract: World-action models (WAMs) jointly model future observations and actions, typically predicting the future as RGB images. Other visual modalities such as

Multi-Label Proportion Learning for Sea-Ice Type Prediction

arXiv:2609.16347v1 Announce Type: new Abstract: Sea-ice type prediction is important for climate monitoring, maritime navigation, and decision-making in polar regions. The main source of label data fo

Tutorials

Multi-View Foundation Models

arXiv:2512.15708v2 Announce Type: replace Abstract: Foundation models are vital tools in various Computer Vision applications. They take as input a single RGB image and output a deep feature represent

tutorialsarxiv-cs-cv

Nepali Legal Expertise through Generative and Extractive Pre-trained Transformers (NepLEGiT)

arXiv:2609.16010v1 Announce Type: new Abstract: The complexity of legal language and limited accessibility to legal information pose significant challenges to justice delivery in Nepal. Traditional le

applicationsarxiv-cs-cl

NepKANUN: A RAG-Based Nepali Legal Assistant

arXiv:2609.15999v1 Announce Type: new Abstract: Accessing legal information in Nepal is difficult due to complex terminology, limited resources, and misinformation. We introduce an AI-powered legal as

applicationsarxiv-cs-cl

Overcoming technical adoption barriers for mobile service robots in rehabilitation

arXiv:2609.16996v1 Announce Type: new Abstract: Many publications on robotic systems in healthcare describe early-stage work on low technology readiness levels. This paper describes how a mobile servi

Signed p-adic Residual Encodings of Finite-Domain All-Different Systems with a Sudoku Case Study

arXiv:2609.16063v1 Announce Type: new Abstract: We study signed, weighted affine p-adic residual objectives as native encodings of finite-domain constraints. For primes that separate the finite alphab

Talking Head Synthesis with Facial Landmark Guidance via 3D Gaussian Splatting

arXiv:2609.17422v1 Announce Type: new Abstract: Audio-driven digital human generation plays an important role in virtual communication, immersive interaction, and media production. With the developmen

Tendon-Driven Continuum Robot with Modular Stiffness and In-Situ Self Pose Estimation

arXiv:2609.16256v1 Announce Type: new Abstract: Continuum robots enable smooth shape morphing and safe interaction in confined environments. However, most existing systems are task-specific and depend

The Download: AI’s trillion-dollar gamble and OpenAI’s biology data bid

applicationsmit-tech-review

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. What’s at stake in AI’s trillion-dollar gamble When Jessica Wa

The Evolution of Coordination in a Collective Intelligence System: 25 Years of English Wikipedia and the Emergence of Generative AI

arXiv:2609.16856v1 Announce Type: cross Abstract: English Wikipedia is one of the largest examples of collective intelligence on the Web, sustained not only by article production but also by volunteer

the risks WERE foreseeable; i foresaw them. repeatedly, focusing specifically on the risks of LLMs and cybersecurity. happy to provide recei…

applicationsgary-marcus--x

the risks WERE foreseeable; i foresaw them. repeatedly, focusing specifically on the risks of LLMs and cybersecurity. happy to provide receipts on request. I’m not a lawyer, but Sam Altman and Dario A

The Role of Implicit and Explicit Demographic Signals in Large Language Model-based Student Assessment

arXiv:2609.16993v1 Announce Type: cross Abstract: Large Language Models are now common in student assessment, but we know little about how student demographics affect their use. Sometimes, considering

The state of public AI benchmarking is dire and is undermining our ability to understand how good AI is now. Most famous measures are maxed …

applicationsethan-mollick--x

The state of public AI benchmarking is dire and is undermining our ability to understand how good AI is now. Most famous measures are maxed out, and, as this paper shows, the non-saturated benchmarks

This is an excellent demo of an AI model designed to rapidly classify information according to decision rules, much faster and cheaper than …

applicationsethan-mollick--x

This is an excellent demo of an AI model designed to rapidly classify information according to decision rules, much faster and cheaper than an LLM. It is not an LLM itself and cannot output text or co

Research

Time-warping estimation via stationarity-based learning of the de-warped signal

arXiv:2609.16796v1 Announce Type: cross Abstract: Time-warping estimation is a fundamental problem in signal processing with applications in bioacoustics, radar, and biomedical analysis. This paper in

researcharxiv-cs-lg

WholeBodyWAM: Generalizing Pre-trained World-Action Priors to Humanoid Loco-Manipulation via WBC-Grounded Coordination

arXiv:2609.16644v1 Announce Type: new Abstract: World Action Models (WAMs) offer a promising approach to general-purpose robot manipulation by jointly modeling visual dynamics and actions. However, mo

XRoboToolKit-T: Teleoperation with High Stability and Precision with Tactile Sensing for Contact-rich Manipulation

arXiv:2609.16437v1 Announce Type: new Abstract: Collecting high-quality robot data for contact-rich manipulation tasks is essential for enabling robots to acquire real-world skills. However, existing

A Conservative OCR-Enabled Workflow for R214 Sodium Screening of South African Packaged Foods

arXiv:2609.15427v1 Announce Type: cross Abstract: Using food package images to monitor sodium and salt content against South Africa's R214 sodium limits is challenging when screening decisions require

A New Transformer-Based Approach for Audio-Based Kinship Verification and a New Uncontrolled Mandarin Kinship Speech Dataset

arXiv:2609.14145v1 Announce Type: cross Abstract: Kinship verification is a task involving determining whether two individuals share a first-order kin relation. To tackle this task, we propose CONVTRA

Agents

A primer on evaluation methods for large language models in healthcare

arXiv:2609.14819v1 Announce Type: cross Abstract: Large language models (LLMs) have a growing range of applications in medicine, and their evaluation is critical for ensuring they provide benefit and

agentsarxiv-cs-ai

A technology-oriented mapping of the language and translation industry: Analysing stakeholder values and their potential implication for translation pedagogy

arXiv:2603.11667v3 Announce Type: replace Abstract: This paper examines how value is constructed and negotiated in today's increasingly automated language and translation industry. Drawing on intervie

applicationsarxiv-cs-cl

A Vision Based Framework Integrating Attention and Action Cues for Interpretable Cognitive Workload Assessment in Human Robot Collaborative Assembly

arXiv:2609.15232v1 Announce Type: new Abstract: The introduction of human-robot collaboration (HRC) in industrial assembly operations is revolutionizing the manufacturing landscape. In this evolving e

AlgoRAG: Retrieval-Augmented Generation for Theoretical Computer Science Education -- A Comprehensive Evaluation Framework for Algorithm Analysis and Complexity Theory

arXiv:2609.14572v1 Announce Type: cross Abstract: Teaching abstract theoretical computer science (TCS) concepts such as algorithm analysis and complexity theory is challenging because students must ha

Backward SDEs-based Diffusion for Physics-Constrained Generation

arXiv:2609.15702v1 Announce Type: new Abstract: Pretrained score-based diffusion models provide strong unconditional priors, yet enforcing measurement or physics consistency in inverse problems is oft

Beyond OCR Accuracy: Text-Centric VQA Under Image Degradation with Modular and End-to-End

arXiv:2609.13815v1 Announce Type: new Abstract: Text-centric Visual Question Answering (VQA) requires reading and reasoning over text embedded in images, a task made substantially harder when images s

applicationsarxiv-cs-cv

Research

Beyond Quacking: Deep Integration of Language Models and RAG into DuckDB

arXiv:2504.01157v1 Announce Type: cross Abstract: Knowledge-intensive analytical applications retrieve context from both structured tabular data and unstructured, text-free documents for effective dec

researcharxiv-cs-ai

Can Skills Learned in Games Transfer to Real-World Work?

Good Start Labs experiments show that AI training with gameplay can lead to transferable skills: a version trained on a railroad simulation outperformed peers in financial research. Inspired by Twitch

applicationslatent-space

CHAI for LLMs: Improving Code-Mixed Translation in Large Language Models through Reinforcement Learning with AI Feedback

arXiv:2411.09073v4 Announce Type: replace-cross Abstract: Large language models (LLMs) show strong performance across many tasks but remain weak at understanding code-mixed (CM) language. Despite this

Context-Aware Mutual Learning for Blind Image Inpainting and Beyond

arXiv:2609.14439v1 Announce Type: new Abstract: Blind image inpainting, aiming to recover contaminated images in the case of unknown masks, is a challenging task. Motivated by the perspective of human

applicationsarxiv-cs-cv

CRITICS - Critical Science Without Borders: Language Models to Promote Critical Thinking in Science Education

arXiv:2609.13942v1 Announce Type: cross Abstract: The CRITICS project addresses science accessibility and literacy by converging advanced Machine Translation (MT) based on Large Language Models (LLMs)

Degraded but Not Entirely Ineffective: PE-Based Deformable Graph Neural Networks

arXiv:2609.13712v1 Announce Type: new Abstract: Many real-world scenarios can be represented using graph-structured data. However, traditional GNNs that transmit messages based on first-order neighbor

DIDO: Distilling Interaction-Centric Dynamics into One-Step Denoising for World Action Models

arXiv:2609.15570v1 Announce Type: new Abstract: World Action Models (WAMs) use video generation models to predict future visual dynamics for robotic manipulation, but iterative denoising introduces ad

Model Releases

Diffusion-Based Multiple-Shooting Indirect Optimal Control for Fuel-Optimal Spacecraft Trajectory Generation

model-releasesarxiv-cs-lg

arXiv:2609.13990v1 Announce Type: cross Abstract: Diffusion-based generative models (DMs) have found applications in control problems, and in particular robotics, where the DMs enable exploration of p

Discovering Hierarchy-Grounded Domains with Adaptive Granularity for Clinical Domain Generalization

arXiv:2506.06977v4 Announce Type: replace-cross Abstract: Domain generalization has become a critical challenge in predictive healthcare, where different patient groups exhibit shifting data distribut

DuctAM: A Duct-Assisted Quadrotor-Based Aerial Manipulator Enabling High-Force Push-and-Pull Interactions

arXiv:2609.15861v1 Announce Type: new Abstract: Uncrewed Aerial Manipulators (UAMs) extend the capabilities of Uncrewed Aerial Vehicles (UAVs) from perception to physical interaction. Among various ae

Dynamic Learning Solutions: A System for Personalized Educational Video Generation

arXiv:2609.14408v1 Announce Type: new Abstract: We present an automated pipeline that converts NCERT textbooks into interactive video explanations that respond directly to user queries. A user uploads

EdgeHAR: An Edge-Native Compact Sensor Foundation Model for Human Activity Recognition

arXiv:2609.14498v1 Announce Type: cross Abstract: Sensor-based human activity recognition (HAR) is fundamental to ubiquitous and wearable computing, yet existing foundation models are largely designed

Ergodic Trajectory Planning with Dynamic Sensor Footprints

arXiv:2512.08661v2 Announce Type: replace Abstract: This paper addresses the problem of trajectory planning for information gathering with a dynamic and resolution-varying sensor footprint. Ergodic pl

Safety

Evaluating covariate balance for long time horizon Markov decision processes

arXiv:2607.15080v2 Announce Type: replace Abstract: This article explores the application of covariate balance diagnostics for detecting the presence of hidden confounding/model miss-specification in

safetyarxiv-cs-lg

Event-Level Emotion Recognition in the Wild Using Deep Facial Expression Analysis

arXiv:2609.13854v1 Announce Type: new Abstract: Facial emotion recognition (FER) in real-world environments remains challenging due to unconstrained imaging conditions, including multiple faces, occlu

applicationsarxiv-cs-cv

Tutorials

Generalized Correctness Models: Learning Calibrated and Model-Agnostic Correctness Predictors from Historical Patterns

arXiv:2509.24988v2 Announce Type: replace-cross Abstract: Generating accurate and calibrated confidence estimates is critical for deploying LLMs in high-stakes or user-facing applications, and remains

tutorialsarxiv-cs-ai

GeomVLA: Unifying Scene, Motion, and Action in 3D

arXiv:2609.13812v1 Announce Type: new Abstract: We present GeomVLA, a Vision-Language-Action (VLA) model that unifies perception, latent scene motion prediction, and action generation within a shared

How Well Do Pseudo-Rigid Body Models Capture Real Plants? In-Field Validation of Simulated Blueberry Canes

arXiv:2609.13627v1 Announce Type: new Abstract: Many labor-intensive tasks in fruit production such as pruning require physically interacting with the plant (e.g., pushing, pulling, bending limbs, etc

IntraGuard: Committee-Side Defenses Against Review Outsourcing to Commercial Chatbots

arXiv:2605.05271v2 Announce Type: replace-cross Abstract: LLMs become increasingly capable, editorial boards and program committees are growing concerned about reviewers who fully outsource peer revie

Introspective Uncertainty Estimation for LLM-Based Code Generation

arXiv:2609.13975v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used for code generation but can produce fluent yet functionally incorrect outputs, which limits trust i