We present our new paper 'Geographic Citation Gaps in NLP Research'
In this #EMNLP2022 work, we examine the relationship between geographical location and publication impact in the field of NLP.
arxiv.org/abs/2210.14424
Janvijay Singh Diyi Yang Machine Learning at Georgia Tech Stanford NLP Group
#NLProc
What a poster session: Thank you all for stopping by!
If you missed it and want to know the secret on how to choose the best LM for your task without fine-tuning, find us (Max Mike Zhang Barbara Plank) around the conference in the next days 😁👋
#EMNLP2022
While I'm not at #EMNLP2022 , we have two works on the intersection of RL + NLP.
RLPrompt: Optimizing Discrete Text Prompts with Reinforcement Learning
(arxiv.org/abs/2205.12548)
Efficient (Soft) Q-Learning for Text Generation with Limited Good Data
(arxiv.org/abs/2106.07704)
What machine translation errors are evaluation metrics sensitive to and to what extent? Check out DEMETR - dataset to diagnose MT evaluation metrics #EMNLP2022 (P4 Board 1) work with Nishant Raj Katherine Thai Yixiao Song Ankita Gupta Mohit Iyyer (1/5)
📜Paper arxiv.org/abs/2210.13746
Machine rationales are generated to explain LM behavior, but to what extent can they be *utilized* to improve LMs’ OOD generalization? 🤔
Our 🏥ER-Test paper ( #EMNLP2022 Findings + #BlackboxNLP ) investigates this question! 🔍
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Slowly coming back to earth (+ timezone) after a fantastic time at #emnlp2022 . It's truly a privilege to get to spend a week nerding out with colleagues and catching up with friends while exploring a new destination. Looking forward to many more!
✈️ I will be at #EMNLP2022 in Abu Dhabi where my colleagues and I present several works at the main conference, Findings as well as the GEM workshop. Details below: 🧵(1/5)
Finally, I met Yejin Choi at the conference!Thank you for accepting the photo request. I met her at the Ritz-Carlton with a view of the beautiful mosque last night. I was so honored that I couldn't sleep! As a Korean, I am proud of her! Yejin Choi #EMNLP2022
Mind-blowing paper I met on #EMNLP2022 . I highly recommend this paper. The idea is so cool that I can't help to check out the code directly after having a chat with the cool author Oren Sultan!
#EMNLP2022 livetweet
Are hard data samples also harder to explain? Does GPT-3 explain data labels as well as humans for both easy & hard samples?
Our #EMNLP2022 paper studies the connection between explainability & sample hardness!
Peter Hase Nazneen Rajani Mohit Bansal
arxiv.org/abs/2211.07517
🧵
I am attending+enjoying #EMNLP2022 in Abu Dhabi & will be presenting our talk on 'explanation hardness' in Interpretability Oral session on Dec11 at 9AM Local time! Come join us😃
Peter Hase Nazneen Rajani Mohit Bansal
Talk: underline.io/events/342/ses…
arxiv.org/abs/2211.07517
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