Papers by Gautam Kumar
Counter Turing Test (CT2): AI-Generated Text Detection is Not as Easy as You May Think - Introducing AI Detectability Index (ADI) (2023.emnlp-main)
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Megha Chakraborty, S.M Towhidul Islam Tonmoy, S M Mehedi Zaman, Shreya Gautam, Tanay Kumar, Krish Sharma, Niyar Barman, Chandan Gupta, Vinija Jain, Aman Chadha, Amit Sheth, Amitava Das
| Challenge: | a number of issues have arisen regarding the risk and consequences of AI-generated text detection. |
| Approach: | They propose a counter-turing test to evaluate the robustness of existing AGTD methods . they propose ADI, a quantifiable spectrum to assess detectability of LLMs . |
| Outcome: | The proposed method evaluates the robustness of existing AGTD methods . it shows that larger LLMs tend to have lower ADI, indicating they are less detectable . |
Intent Detection and Discovery from User Logs via Deep Semi-Supervised Contrastive Clustering (2022.naacl-main)
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| Challenge: | Existing approaches to intent detection rely on epoch wise clustering and classification based on labeled and unlabeled data. |
| Approach: | They propose an end-to-end deep contrastive clustering algorithm that jointly updates model parameters and cluster centers via supervised and self-supervised learning. |
| Outcome: | The proposed approach outperforms baselines on five public datasets and human-in-the-loop variant for practical deployment. |
Prompt Augmented Generative Replay via Supervised Contrastive Learning for Lifelong Intent Detection (2022.findings-naacl)
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| Challenge: | Existing methods to identify all possible user intents at design time are expensive and require storage of past data. |
| Approach: | They propose to continually train an intent detector on new intents while maintaining performance on prior intents. |
| Outcome: | The proposed method outperforms exemplar replay-based approaches on lifelong intent detection tasks and achieves state-of-the-art on four public datasets. |
A Large-Scale Japanese Dataset for Aspect-based Sentiment Analysis (2022.lrec-1)
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| Challenge: | Aspect-based sentiment analysis (ABSA) has not been explored in the Japanese language . there is no standard Japanese dataset available for ABSA task in the language - a paper by cnn. |
| Approach: | They propose to use a Japanese aspect-based sentiment analysis dataset for hotel reviews domain . they propose to include 53,192 review sentences with seven aspect categories and two polarity labels . |
| Outcome: | The proposed dataset contains 53,192 review sentences with seven aspect categories and two polarity labels. |
Hunt for Buried Treasures: Extracting Unclaimed Embodiments from Patent Specifications (2023.acl-industry)
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| Challenge: | Unclaimed embodiment extraction is performed manually and little research has been conducted on its automation. |
| Approach: | They propose a task of unclaimed embodiment extraction and a dataset for the task . they use a natural language inference task to extract unclaimed inventions . |
| Outcome: | The proposed task requires performing natural language inference on patent specifications. |