1 code implementation • 11 Nov 2024 • Howard Chen, Jiayi Geng, Adithya Bhaskar, Dan Friedman, Danqi Chen
REMIX prevents forgetting by mixing generic data sampled from pretraining corpora or even randomly generated word sequences during each stage, despite being unrelated to the memorized factoids in the first stage.
1 code implementation • 26 Jun 2024 • ZiRui Wang, Mengzhou Xia, Luxi He, Howard Chen, Yitao Liu, Richard Zhu, Kaiqu Liang, Xindi Wu, Haotian Liu, Sadhika Malladi, Alexis Chevalier, Sanjeev Arora, Danqi Chen
All models lag far behind human performance of 80. 5%, underscoring weaknesses in the chart understanding capabilities of existing MLLMs.
1 code implementation • 16 Feb 2024 • Alexis Chevalier, Jiayi Geng, Alexander Wettig, Howard Chen, Sebastian Mizera, Toni Annala, Max Jameson Aragon, Arturo Rodríguez Fanlo, Simon Frieder, Simon Machado, Akshara Prabhakar, Ellie Thieu, Jiachen T. Wang, ZiRui Wang, Xindi Wu, Mengzhou Xia, Wenhan Xia, Jiatong Yu, Jun-Jie Zhu, Zhiyong Jason Ren, Sanjeev Arora, Danqi Chen
We use TutorChat to fine-tune Llemma models with 7B and 34B parameters.
no code implementations • 8 Oct 2023 • Howard Chen, Ramakanth Pasunuru, Jason Weston, Asli Celikyilmaz
Large language models (LLMs) have advanced in large strides due to the effectiveness of the self-attention mechanism that processes and compares all tokens at once.
1 code implementation • 17 Jul 2023 • Shunyu Yao, Howard Chen, Austin W. Hanjie, Runzhe Yang, Karthik Narasimhan
Text generation under constraints have seen increasing interests in natural language processing, especially with the rapidly improving capabilities of large language models.
1 code implementation • 24 May 2023 • Ameet Deshpande, Carlos E. Jimenez, Howard Chen, Vishvak Murahari, Victoria Graf, Tanmay Rajpurohit, Ashwin Kalyan, Danqi Chen, Karthik Narasimhan
Semantic textual similarity (STS), a cornerstone task in NLP, measures the degree of similarity between a pair of sentences, and has broad application in fields such as information retrieval and natural language understanding.
1 code implementation • 16 May 2023 • Jane Pan, Tianyu Gao, Howard Chen, Danqi Chen
Large language models (LLMs) exploit in-context learning (ICL) to solve tasks with only a few demonstrations, but its mechanisms are not yet well-understood.
no code implementations • 20 Dec 2022 • Howard Chen, Huihan Li, Danqi Chen, Karthik Narasimhan
We consider the task of text generation in language models with constraints specified in natural language.
2 code implementations • 4 Jul 2022 • Shunyu Yao, Howard Chen, John Yang, Karthik Narasimhan
Existing benchmarks for grounding language in interactive environments either lack real-world linguistic elements, or prove difficult to scale up due to substantial human involvement in the collection of data or feedback signals.
1 code implementation • NAACL 2022 • Howard Chen, Jacqueline He, Karthik Narasimhan, Danqi Chen
Our experiments reveal that the rationale models show the promise to improve robustness, while they struggle in certain scenarios--when the rationalizer is sensitive to positional bias or lexical choices of attack text.
1 code implementation • NAACL 2021 • Howard Chen, Mengzhou Xia, Danqi Chen
One significant challenge in supervised all-words WSD is to classify among senses for a majority of words that lie in the long-tail distribution.
2 code implementations • NAACL 2021 • Derek Chen, Howard Chen, Yi Yang, Alex Lin, Zhou Yu
Existing goal-oriented dialogue datasets focus mainly on identifying slots and values.
no code implementations • 12 Jan 2021 • Howard Chen, Zhuchang Zhan, Allison Youngblood, Eric T. Wolf, Adina D. Feinstein, Daniel E. Horton
Low-mass stars show evidence of vigorous magnetic activity in the form of large flares and coronal mass ejections.
Earth and Planetary Astrophysics Solar and Stellar Astrophysics
2 code implementations • EMNLP 2020 • Alexander Lin, Jeremy Wohlwend, Howard Chen, Tao Lei
The performance of autoregressive models on natural language generation tasks has dramatically improved due to the adoption of deep, self-attentive architectures.
Ranked #22 on
Machine Translation
on IWSLT2014 German-English
1 code implementation • ACL 2020 • Lili Yu, Howard Chen, Sida Wang, Tao Lei, Yoav Artzi
We study the potential for interaction in natural language classification.
4 code implementations • CVPR 2019 • Howard Chen, Alane Suhr, Dipendra Misra, Noah Snavely, Yoav Artzi
We study the problem of jointly reasoning about language and vision through a navigation and spatial reasoning task.
Ranked #11 on
Vision and Language Navigation
on Touchdown Dataset