We present WebGLM, a web-enhanced question-answering system based on the General Language Model (GLM). Its goal is to augment a pre-trained large language model (LLM) with web search and retrieval capabilities while being efficient for real-world ...

Understanding visually-rich business documents to extract structured data and automate business workflows has been receiving attention both in academia and industry. Although recent multi-modal language models have achieved impressive results, we find ...

Pre-trained language models (PLMs) are fundamental for natural language processing applications. Most existing PLMs are not tailored to the noisy user-generated text on social media, and the pre-training does not factor in the valuable social engagement ...

Bipolar disorder (BD) is closely associated with an increased risk of suicide. However, while the prior work has revealed valuable insight into understanding the behavior of BD patients on social media, little attention has been paid to developing a ...

We study the ability of transformer-based language models (LMs) to understand social media language. Social media (SM) language is distinct from standard written language, yet existing benchmarks fall short of capturing LM performance in this socially, ...

In this study, we present a Bangla multi-domain sentiment analysis dataset, named as SentiGOLD, developed using 70,000 samples, which was compiled from a variety of sources and annotated by a gender-balanced team of linguists. This dataset was created ...

Social media is awash with hateful content, much of which is often veiled with linguistic and topical diversity. The benchmark datasets used for hate speech detection do not account for such divagation as they are predominantly compiled using hate ...

Recent years have witnessed the rapid development of machine-learning-based intelligent recruitment services. Along this line, a large number of emerging models have been proposed, achieving remarkable performance in various tasks, such as person-job fit,...

In digital marketing, experimenting with new website content is one of the key levers to improve customer engagement. However, creating successful marketing content is a manual and time-consuming process that lacks clear guiding principles. This paper ...

The ease of spreading false information online enables individuals with malicious intent to manipulate public opinion and destabilize social stability. Recently, fake news detection based on evidence retrieval has gained popularity in an effort to ...

Cross-lingual natural language understanding~(NLU) aims to train NLU models on a source language and apply the models to NLU tasks in target languages, and is a fundamental task for many cross-language applications. Most of the existing cross-lingual ...

Graph neural networks (GNNs) have shown high potential for a variety of real-world, challenging applications, but one of the major obstacles in GNN research is the lack of large-scale flexible datasets. Most existing public datasets for GNNs are ...

We present GLM-Dialog, a large-scale language model (LLM) with 10B parameters capable of knowledge-grounded conversation in Chinese using a search engine to access the Internet knowledge. GLM-Dialog offers a series of applicable techniques for exploiting ...

The realm of scientific text summarization has experienced remarkable progress due to the availability of annotated brief summaries and ample data. However, the utilization of multiple input modalities, such as videos and audio, has yet to be thoroughly ...

A final exam in machine learning at a top institution such as MIT, Harvard, or Cornell typically takes faculty days to write, and students hours to solve. We demonstrate that large language models pass machine learning finals at a human level on finals ...

Query AutoComplete (QAC) or AutoSuggest is the first place of user interaction with an e-commerce search engine. It is critical for the QAC system to suggest relevant and well-formed queries for multiple possible user intents. Suggesting only the ...

Text-editing models have recently become a prominent alternative to seq2seq models for monolingual text-generation tasks such as grammatical error correction, simplification, and style transfer. These tasks share a common trait -- they exhibit a large ...

Virtual Intelligent Assistants take user requests in the voice form, perform actions such as setting an alarm, turning on a light, and answering a question, and provide answers or confirmations in the voice form or through other channels such as a ...

Language representations pretrained on general-domain corpora and adapted to downstream task data have achieved enormous success in building natural language understanding (NLU) systems. While the standard supervised fine-tuning of pretrained language ...

Medicine today is imprecise. Among the top 20 drugs in the U.S., up to 80% of patients are non-responders. The goal of precision health is to provide the right intervention for the right people at the right time. The key to realize this dream is to ...