6 citations · 10 across the 8 of their papers we have counts for
7 papers · 1 filter
Tailoring Self-Rationalizers with Multi-Reward Distillation
Sahana Ramnath, Brihi Joshi, Skyler Hallinan +6
Large language models (LMs) are capable of generating free-text rationales to aid question answering. However, prior work 1) suggests that useful self-rationalization is emergent o…
Are Machine Rationales (Not) Useful to Humans? Measuring and Improving Human Utility of Free-Text Rationales
Brihi Joshi, Ziyi Liu, Sahana Ramnath +6
Among the remarkable emergent capabilities of large language models (LMs) is free-text rationalization; beyond a certain scale, large LMs are capable of generating seemingly useful…
KNIFE: Distilling Reasoning Knowledge From Free-Text Rationales
Aaron Chan, Zhiyuan Zeng, Wyatt Lake +3
Language models (LMs) have yielded impressive results on many language reasoning tasks, but their unexpected errors raise doubts about their reasoning abilities. In light of this,…
XMD: An End-to-End Framework for Interactive Explanation-Based Debugging of NLP Models
Dong-Ho Lee, Akshen Kadakia, Brihi Joshi +8
NLP models are susceptible to learning spurious biases (i.e., bugs) that work on some datasets but do not properly reflect the underlying task. Explanation-based model debugging ai…
ER-Test: Evaluating Explanation Regularization Methods for Language Models
Brihi Joshi, Aaron Chan, Ziyi Liu +4
By explaining how humans would solve a given task, human rationales can provide strong learning signal for neural language models (LMs). Explanation regularization (ER) aims to imp…
The Devil is in the Details: Evaluating Limitations of Transformer-based Methods for Granular Tasks
Brihi Joshi, Neil Shah, Francesco Barbieri +1
Contextual embeddings derived from transformer-based neural language models have shown state-of-the-art performance for various tasks such as question answering, sentiment analysis…
Generating Clues for Gender based Occupation De-biasing in Text
Nishtha Madaan, Gautam Singh, Sameep Mehta +2
Vast availability of text data has enabled widespread training and use of AI systems that not only learn and predict attributes from the text but also generate text automatically.…