All papers

This paper presents a framework and a dataset to generate holistic full-body co-speech gestures from audio and masked movement priors.

This paper introduces frequency assignment techniques using partially overlapped channels to improve spectral efficiency in integrated access and backhaul networks.

This paper surveys foundation models, agent systems, datasets, and computational tools applied to materials science discovery.

This paper surveys foundation models, agent systems, datasets, and computational tools applied to materials science discovery.

This paper surveys foundation models, agent systems, datasets, and computational tools applied to materials science discovery.

This paper surveys foundation models, agent systems, datasets, and computational tools applied to materials science discovery.

The paper evaluates twenty-one language models used as judges across three benchmarks, finding widespread discrepancies between agreement metrics and underlying validity.

The paper evaluates twenty-one language models used as judges across three benchmarks, finding widespread discrepancies between agreement metrics and underlying validity.

The paper evaluates twenty-one language models used as judges across three benchmarks, finding widespread discrepancies between agreement metrics and underlying validity.

The paper evaluates twenty-one language models used as judges across three benchmarks, finding widespread discrepancies between agreement metrics and underlying validity.

The paper evaluates twenty-one language models used as judges across three benchmarks, finding widespread discrepancies between agreement metrics and underlying validity.

The paper evaluates twenty-one language models used as judges across three benchmarks, finding widespread discrepancies between agreement metrics and underlying validity.

The paper analyzes extreme faults in modular multilevel converters and proposes a protection scheme using integrated gate-commutated thyristors.

The paper presents a network utilizing self-attention and spatio-temporal convolutions for 3D skeleton-based human action recognition.

The paper proposes an uncertainty-aware multimodal descriptor fusing sequential camera and LiDAR data for robotic place recognition.

The paper develops a microprocessor-based smart wearable glass system with GPS monitoring to assist visually impaired individuals.

The paper proposes a metamorphic testing method with mutation operators to evaluate how retrieval-augmented generation systems handle changing document corpora.

The paper models epileptic dynamics using a multi-stable system to detect critical slowing down and design feedback control for seizure prevention.

The paper examines vulnerabilities of deepfake detection models to backdoor attacks and evaluates related defense strategies.

The paper studies cybersecurity threat detection using sequential deep learning models evaluated on the KDD network traffic dataset.

The paper summary contains webpage metadata rather than research text, though it mentions partial discharge localization for drone inspection using UHF detection.

The paper evaluates machine learning models, finding Random Forest predicts depression in menopausal women with high accuracy.

The paper proposes parallel delay chains to enable low-power neuromorphic circuits to detect anomalies in long electrocardiogram signals.

The paper provides a synthetic dataset to detect passive wireless jamming attacks carried out using reconfigurable intelligent surfaces.

The paper proposes an adaptive strategy using software agents and competency-based ontologies to assist students in e-learning platforms.

The paper presents a spatio-temporal attention framework to predict trajectories of multiple mixed agents in unsignalized traffic roundabouts.

The text contains publisher metadata and page navigation text without readable abstract details about the InsightChain supplier discovery agent.

The paper presents an autonomous framework using multiagent reinforcement learning to monitor, diagnose, and recover from failures in production AI systems.

The authors introduce CharXiv, a benchmark of realistic scientific charts designed to test descriptive and reasoning capabilities in multimodal language models.

The authors introduce CharXiv, a benchmark of realistic scientific charts designed to test descriptive and reasoning capabilities in multimodal language models.

The authors introduce CharXiv, a benchmark of realistic scientific charts designed to test descriptive and reasoning capabilities in multimodal language models.

The authors introduce CharXiv, a benchmark of realistic scientific charts designed to test descriptive and reasoning capabilities in multimodal language models.

The authors introduce CharXiv, a benchmark of realistic scientific charts designed to test descriptive and reasoning capabilities in multimodal language models.

The authors introduce CharXiv, a benchmark of realistic scientific charts designed to test descriptive and reasoning capabilities in multimodal language models.

This survey provides an algorithmic overview and failure mode analysis of reinforcement learning techniques applied to language models.

This survey provides an algorithmic overview and failure mode analysis of reinforcement learning techniques applied to language models.

This survey provides an algorithmic overview and failure mode analysis of reinforcement learning techniques applied to language models.

This paper reports the fabrication and continuous-wave optical performance of laterally coupled distributed feedback semiconductor lasers.

This paper evaluates a buffer-free transistor structure designed to suppress current drift and lag in high-power electronics.

This paper surveys capacitance-voltage measurement techniques to evaluate defect states and reliability in gallium nitride transistor devices.

This paper presents an empirical study evaluating open-source language models for automated unit test generation in software development.

This paper proposes a discrete diffusion model for controllable visual layout generation under structural element constraints.

This paper proposes a discrete diffusion model for controllable visual layout generation under structural element constraints.

This paper proposes a discrete diffusion model for controllable visual layout generation under structural element constraints.

This paper evaluates the ability of language models to generate non-functional requirements from functional software specifications.

This paper evaluates the ability of language models to generate non-functional requirements from functional software specifications.

This paper evaluates the ability of language models to generate non-functional requirements from functional software specifications.

This paper evaluates the ability of language models to generate non-functional requirements from functional software specifications.

This paper introduces an open-source multi-agent system designed to generate, verify, and debug hardware description code.

This paper introduces an evaluation benchmark using multimodal models to assess generated videos across human preference dimensions.

This paper introduces an evaluation benchmark using multimodal models to assess generated videos across human preference dimensions.

This paper introduces an evaluation benchmark using multimodal models to assess generated videos across human preference dimensions.

This paper introduces an evaluation benchmark using multimodal models to assess generated videos across human preference dimensions.

This paper combines evolutionary computation with language models to optimize register-transfer level hardware code for correctness and efficiency.

This paper combines evolutionary computation with language models to optimize register-transfer level hardware code for correctness and efficiency.

This paper combines evolutionary computation with language models to optimize register-transfer level hardware code for correctness and efficiency.

This paper combines evolutionary computation with language models to optimize register-transfer level hardware code for correctness and efficiency.

This paper surveys synthetic data generation and data augmentation techniques for machine learning with an emphasis on healthcare.

This paper introduces specification templates to define operational boundaries, authority, and oversight for autonomous software agents.

This paper introduces specification templates to define operational boundaries, authority, and oversight for autonomous software agents.