Results 151 to 160 of about 52,458 (341)

Smart Nanotechnologies for Multimodal Neuromodulation and Brain Interfacing

Advanced Science, EarlyView.
Recent advances in smart nanotechnologies are expanding the toolbox for brain interfacing, from wireless neuromodulation and high‐resolution sensing to targeted delivery within the central nervous system. By combining responsive nanomaterials with bioinspired design, these platforms enable multimodal interactions with neurons and glia, while also ...
Tommaso Curiale, Marie Celine Lefevre, Alessio Carmignani, Maria Cristina Ceccarelli, Matteo Battaglini, Attilio Marino, Gianni Ciofani   +6 more
wiley   +1 more source

ExBERT: An External Knowledge Enhanced BERT for Natural Language Inference [PDF]

, 2021
Amit Gajbhiye, Noura Al Moubayed, Steven Bradley   +2 more
openalex   +1 more source

Logic, inference, understanding: cross-domain generalization for generative language models

Frontiers in Artificial Intelligence
Neural systems for Natural Language Inference (NLI) have seen impressive performance over the last ten years, but their ability to generalize beyond their training data has repeatedly been questioned.
Rasmus Blanck, Bill Noble
doaj   +1 more source

Schooling Trajectories and the Development of Brain Dynamics: A Comparative Study of Montessori and Traditional Education

Advanced Science, EarlyView.
We investigate whether Montessori and traditional schooling systems shape the developmental trajectory of large‐scale brain dynamics in different ways. We quantify the arrow of time (“non‐reversibility”) in neural activity during resting state and movie‐watching, revealing distinct maturational patterns.
Elvira del Agua, Anira Escrichs, Yonatan Sanz Perl, Morten L. Kringelbach, Adele Diamond, Solange Denervaud, Gustavo Deco   +6 more
wiley   +1 more source

Recognizing Textual Inference in Mongolian Bar Exam Questions

Applied Sciences
This paper examines how to apply deep learning techniques to Mongolian bar exam questions. Several approaches that utilize eight different fine-tuned transformer models were demonstrated for recognizing textual inference in Mongolian bar exam questions ...
Garmaabazar Khaltarkhuu, Biligsaikhan Batjargal, Akira Maeda   +2 more
doaj   +1 more source

Embarrassingly Simple Performance Prediction for Abductive Natural Language Inference

The task of natural language inference (NLI), to decide if a hypothesis entails or contradicts a premise, received considerable attention in recent years.
Srivastav, Vaibhav, Kadiķis, Emīls, Klinger, Roman   +2 more
core  

Large-scale connectionist natural language parsing using lexical semantic and syntactic knowledge

, 2007
Syntactic parsing plays a pivotal role in most automatic natural language processing systems. The research project presented in this dissertation has focused on two main characteristics of connectionist models for natural language processing: their ...
Nkantah, DE
core  

Ferroelectric Devices for In‐Memory and In‐Sensor Computing

Advanced Science, EarlyView.
Inspired by biological systems, in‐memory and in‐sensor computing overcome von Neumann bottlenecks. Ferroelectric devices can mimic synaptic functions and sense stimuli like light or force, therefore are ideal for these paradigms. This review introduces the ferroelectric devices applied for in‐memory and in‐sensor computing, covering their structures ...
Hong Fang, Ronghuan Xie, Qiang Cao, Shishen Yan, Xiaolin Wang, Limei Zheng   +5 more
wiley   +1 more source

Lost in Inference: Rediscovering the Role of Natural Language Inference for Large Language Models

Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
In the recent past, a popular way of evaluating natural language understanding (NLU), was to consider a model's ability to perform natural language inference (NLI) tasks. In this paper, we investigate if NLI tasks, that are rarely used for LLM evaluation, can still be informative for evaluating LLMs. Focusing on five different NLI benchmarks across six
Lovish Madaan, David Esiobu, Pontus Stenetorp, Barbara Plank, Dieuwke Hupkes   +4 more
openaire   +2 more sources

KLSBench: Evaluating LLM Capabilities on Korean Literary Sinitic Texts in Historical Context

Applied Sciences
Large language models (LLMs) show limited capability in processing low-resource historical languages due to insufficient training data and domain-specific linguistic structures.
Seung-Hyun Han, Won-Seok Yang, Xiaohan Ma, Tae-Sun Chung   +3 more
doaj   +1 more source