Yes but.. Can ChatGPT Identify Entities in Historical Documents?

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The ability to reason, plan and solve highly abstract problems is a hallmark of human intelligence. Recent advancements in artificial intelligence, propelled by deep neural networks, have revolutionized disciplines like computer vision and natural language ...

Large language models (LLMs) have shown strong performance in tasks across domains but struggle with chemistry-related problems. These models also lack access to external knowledge sources, limiting their usefulness in scientific applications. We introduce ...

Transformer models such as GPT generate human-like language and are predictive of human brain responses to language. Here, using functional-MRI-measured brain responses to 1,000 diverse sentences, we first show that a GPT-based encoding model can predict t ...

Due to the increasing demands of today's fast-paced world, mental health concerns are on the rise, which necessitates innovative approaches to provide support to those in need. Open-domain conversational agents known as chatbots, offer a unique opportunit ...

The recent rise in both popularity and performance of large language models has garnered considerable interest regarding their applicability to education. Technologies like ChatGPT, which can engage in human-like dialog, have already disrupted educational ...

In recent years, the use of chatbots in education has been driven by advances in natural language processing and the increasing availability of digital education platforms. Although the added value of educational chatbots appears promising, researchers hav ...

The presence of conversational agents (or chatbots) in educational contexts has been steadily increasing over the past few years. Recent surveys have shown widespread interest in the use of chatbots in education, both for research and practice. Although th ...

Most recent test-time adaptation methods focus on only classification tasks, use specialized network architectures, destroy model calibration or rely on lightweight information from the source domain. To tackle these issues, this paper proposes a novel Tes ...

Abstractive summarization has seen big improvements in recent years, mostly due to advances in neural language modeling, language model pretraining, and scaling models and datasets. While large language models generate summaries that are fluent, coherent, ...

Chat Generative Pre-trained Transformer (ChatGPT) is currently a trending topic worldwide triggering extensive debate about its predictive power, its potential uses, and its wider implications. Recent publications have demonstrated that ChatGPT can correct ...

Recent transformer language models achieve outstanding results in many natural language processing (NLP) tasks. However, their enormous size often makes them impractical on memory-constrained devices, requiring practitioners to compress them to smaller net ...

This paper introduces TACOSS a text-image alignment approach that allows explainable land cover semantic segmentation by directly integrating semantic concepts encoded from texts. TACOSS combines convolutional neural networks for visual feature extraction ...

In this dissertation, we propose multiple methods to improve transfer learning for pretrained language models (PLMs). Broadly, transfer learning is a powerful technique in natural language processing, where a language model is first pre-trained on a data-r ...

Language has shaped human evolution and led to the desire to endow machines with language abilities. Recent advancements in natural language processing enable us to achieve this breakthrough in human-machine interaction. However, introducing conversational ...

While chatbots are commonly used to support software developers with repetitive tasks, their use in programming education is still limited, particularly for students in non-technical domains. To better understand the potential for chatbots to support progr ...

Natural Language Processing (NLP) has become increasingly utilized to provide adaptivity in educational applications. However, recent research has highlighted a variety of biases in pre-trained language models. While existing studies investigate bias in di ...

Remote sensing visual question answering (RSVQA) opens new avenues to promote the use of satellites data, by interfacing satellite image analysis with natural language processing. Capitalizing on the remarkable advances in natural language processing and c ...

Large language models (LLMs) have demonstrated human-level performance on a vast spectrum of natural language tasks. However, it is largely unexplored whether they can better internalize knowledge from a structured data, such as a knowledge graph, or from ...

Over the past few years, there has been an increase in the use of chatbots for educational purposes. Nevertheless, the chatbot technologies and architectures that are often applied to educational contexts are not necessarily designed for such contexts. Whi ...

Open-domain chatbots engage in natural conversations with the user to socialize and establish bonds. However, designing and developing an effective open-domain chatbot is challenging. It is unclear what qualities of such chatbots most correspond to users' ...

Yes but.. Can ChatGPT Identify Entities in Historical Documents?

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Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

Augmenting large language models with chemistry tools

Driving and suppressing the human language network using large language models

Empathetic Conversational Agents for Distress Support

Prompting Large Language Models to Power Educational Chatbots

Harnessing Rule-Based Chatbots to Support Teaching Python Programming Best Practices

A Conceptual Framework for Integrating Conversational Agents in Digital Education

TeSLA: Test-Time Self-Learning With Automatic Adversarial Augmentation

Interpretable Representation Learning and Evaluation for Abstractive Summarization

ChatGPT takes on the European Exam in Core Cardiology: an artificial intelligence success story?

Revisiting Offline Compression: Going Beyond Factorization-based Methods for Transformer Language Models

Text as a Richer Source of Supervision in Semantic Segmentation Tasks

Improving Generalization of Pretrained Language Models

Towards Novel Evaluation Methods for Social Dialog Systems

Challenges and Opportunities in Integrating Interactive Chatbots into Code Review Exercises: A Pilot Case Study

Bias at a Second Glance: A Deep Dive into Bias for German Educational Peer-Review Data Modeling

Language Transformers for Remote Sensing Visual Question Answering

SKILL: Structured Knowledge Infusion for Large Language Models

A Blueprint for Integrating Task-Oriented Conversational Agents in Education

Key Qualities of Conversational Chatbots - the PEACE Model