Title: Stanford AI Lab Research Papers and Engaging Presentations at ACL 2022
Introduction:
Welcome to the 60th Annual Meeting of the Association for Computational Linguistics (ACL) 2022! This event, which is taking place from May 22nd to May 27th, is an exciting opportunity to explore the latest advancements in computational linguistics. At this conference, you can expect to discover groundbreaking research papers, insightful videos, and informative blogs. We are proud to present the work from SAIL (Stanford Artificial Intelligence Laboratory) that will be featured at ACL 2022. Delve into topics such as pretraining language models with document links, the impact of word order in grammatical role classification, the challenges of measuring embedding similarity for high-frequency words, and much more. Join us in exploring the cutting-edge research happening at Stanford!
Full Article: Title: Stanford AI Lab Research Papers and Engaging Presentations at ACL 2022
60th Annual Meeting of the Association for Computational Linguistics (ACL) 2022: Highlights and Accepted Papers
The 60th Annual Meeting of the Association for Computational Linguistics (ACL) 2022 is currently taking place from May 22nd to May 27th. This event brings together researchers, experts, and enthusiasts in the field of computational linguistics to share their work and advancements. The Stanford Artificial Intelligence Laboratory (SAIL) is actively participating in the conference, and here are some of the accepted papers and highlights from their research:
1. LinkBERT: Pretraining Language Models with Document Links
The paper “LinkBERT: Pretraining Language Models with Document Links” by Michihiro Yasunaga, Jure Leskovec, and Percy Liang explores the use of document links for pretraining language models. The authors investigate the impact of incorporating hyperlinks in the pretraining process and its effects on knowledge acquisition.
2. When classifying grammatical role, BERT doesn’t care about word order… except when it matters
Isabel Papadimitriou, Richard Futrell, and Kyle Mahowald present a paper titled “When classifying grammatical role, BERT doesn’t care about word order… except when it matters.” Their research explores the behavior of large language models, specifically BERT, in analyzing word order invariance and its role in classifying grammatical roles.
3. Problems with Cosine as a Measure of Embedding Similarity for High-Frequency Words
Kaitlyn Zhou, Kawin Ethayarajh, Dallas Card, and Dan Jurafsky investigate the limitations of using cosine similarity as a measure of embedding similarity for high-frequency words. Their paper aims to provide insights into the challenges and shortcomings of relying solely on cosine similarity for analyzing embeddings.
4. Text Summarization Evaluation: Beyond ROUGE
Faisal Ladhak, Esin Durmus, He He, Claire Cardie, and Kathleen McKeown present their research on text summarization evaluation. Their paper, titled “Text Summarization Evaluation: Beyond ROUGE,” proposes a novel framework for evaluating text summarization models, focusing on the concept of faithfulness.
5. Spurious Correlations in Reference-Free Evaluation of Text Generation
Esin Durmus, Faisal Ladhak, and Tatsunori Hashimoto explore the issue of spurious correlations in reference-free evaluation of text generation. Their paper sheds light on the challenges and pitfalls in evaluating text generation models, particularly in the context of automated metrics.
These are just a few of the accepted papers from the ACL 2022 conference. Other notable research topics include type-aware bi-encoders for open-domain entity retrieval, few-shot semantic parsers for Wizard-of-Oz dialogues, and the impact of richer representations in richer countries.
The Stanford Artificial Intelligence Laboratory (SAIL) continues to drive innovation and make significant contributions to the growing field of computational linguistics. The researchers’ work demonstrates their commitment to advancing the understanding and application of language processing and artificial intelligence.
To learn more about these papers and the work happening at Stanford, feel free to reach out to the contact authors directly. The ACL 2022 conference is a platform for knowledge sharing and collaboration, and Stanford researchers are eager to engage with fellow researchers and enthusiasts in the field.
Summary: Title: Stanford AI Lab Research Papers and Engaging Presentations at ACL 2022
The 60th Annual Meeting of the Association for Computational Linguistics (ACL) 2022 is currently taking place from May 22nd to May 27th. Stanford’s SAIL team has contributed several papers, videos, and blogs that you can explore. Some of the accepted papers include “LinkBERT: Pretraining Language Models with Document Links,” “When classifying grammatical role, BERT doesn’t care about word order… except when it matters,” “Problems with Cosine as a Measure of Embedding Similarity for High Frequency Words,” “Text Summarization and Generation Evaluation,” and more. These papers cover various topics related to language models, analysis, semantic parsing, entity retrieval, and human-robot interaction, among others. Visit the provided links for more information about each paper.
