Search Results for author: Sahana Ramnath

Found 7 papers, 4 papers with code

Tailoring Self-Rationalizers with Multi-Reward Distillation

1 code implementation6 Nov 2023 Sahana Ramnath, Brihi Joshi, Skyler Hallinan, Ximing Lu, Liunian Harold Li, Aaron Chan, Jack Hessel, Yejin Choi, Xiang Ren

Results on five difficult question-answering datasets StrategyQA, QuaRel, OpenBookQA, NumerSense and QASC show that not only does MaRio improve task accuracy, but it also improves the self-rationalization quality of small LMs across the aforementioned axes better than a supervised fine-tuning (SFT) baseline.

Question Answering StrategyQA

Are Machine Rationales (Not) Useful to Humans? Measuring and Improving Human Utility of Free-Text Rationales

1 code implementation11 May 2023 Brihi Joshi, Ziyi Liu, Sahana Ramnath, Aaron Chan, Zhewei Tong, Shaoliang Nie, Qifan Wang, Yejin Choi, Xiang Ren

Existing metrics like task performance of the LM generating the rationales, or similarity between generated and gold rationales are not good indicators of their human utility.

A Framework for Rationale Extraction for Deep QA models

no code implementations9 Oct 2021 Sahana Ramnath, Preksha Nema, Deep Sahni, Mitesh M. Khapra

As neural-network-based QA models become deeper and more complex, there is a demand for robust frameworks which can access a model's rationale for its prediction.

Explanation Generation Question Answering +1

HintedBT: Augmenting Back-Translation with Quality and Transliteration Hints

no code implementations EMNLP 2021 Sahana Ramnath, Melvin Johnson, Abhirut Gupta, Aravindan Raghuveer

For such cases, we propose training the model with additional hints (as target tags on the decoder) that provide information about the operation required on the source (translation or both translation and transliteration).

Data Augmentation NMT +2

Scene Graph based Image Retrieval -- A case study on the CLEVR Dataset

no code implementations3 Nov 2019 Sahana Ramnath, Amrita Saha, Soumen Chakrabarti, Mitesh M. Khapra

With the prolification of multimodal interaction in various domains, recently there has been much interest in text based image retrieval in the computer vision community.

Graph Matching Image Retrieval +2

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