Search Results for author: Atharva Naik

Found 7 papers, 5 papers with code

Data Augmentation for Code Translation with Comparable Corpora and Multiple References

1 code implementation1 Nov 2023 Yiqing Xie, Atharva Naik, Daniel Fried, Carolyn Rose

One major challenge of translating code between programming languages is that parallel training data is often limited.

Code Translation Data Augmentation +1

Tricking LLMs into Disobedience: Formalizing, Analyzing, and Detecting Jailbreaks

1 code implementation24 May 2023 Abhinav Rao, Sachin Vashistha, Atharva Naik, Somak Aditya, Monojit Choudhury

Recent explorations with commercial Large Language Models (LLMs) have shown that non-expert users can jailbreak LLMs by simply manipulating their prompts; resulting in degenerate output behavior, privacy and security breaches, offensive outputs, and violations of content regulator policies.

Weakly Supervised Explainable Phrasal Reasoning with Neural Fuzzy Logic

1 code implementation18 Sep 2021 Zijun Wu, Zi Xuan Zhang, Atharva Naik, Zhijian Mei, Mauajama Firdaus, Lili Mou

In this work, we address the explainability of NLI by weakly supervised logical reasoning, and propose an Explainable Phrasal Reasoning (EPR) approach.

Explanation Generation Logical Reasoning +2

Understanding the Role of Affect Dimensions in Detecting Emotions from Tweets: A Multi-task Approach

1 code implementation9 May 2021 Rajdeep Mukherjee, Atharva Naik, Sriyash Poddar, Soham Dasgupta, Niloy Ganguly

For the regression task, VADEC, when trained with SenWave, achieves 7. 6% and 16. 5% gains in Pearson Correlation scores over the current state-of-the-art on the EMOBANK dataset for the Valence (V) and Dominance (D) affect dimensions respectively.

Emotion Classification regression +1

How Have We Reacted To The COVID-19 Pandemic? Analyzing Changing Indian Emotions Through The Lens of Twitter

no code implementations20 Aug 2020 Rajdeep Mukherjee, Sriyash Poddar, Atharva Naik, Soham Dasgupta

Since its outbreak, the ongoing COVID-19 pandemic has caused unprecedented losses to human lives and economies around the world.

Emotion Classification

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