Papers by Vijit Malik
ILDC for CJPE: Indian Legal Documents Corpus for Court Judgment Prediction and Explanation (2021.acl-long)
Copied to clipboard
Vijit Malik, Rishabh Sanjay, Shubham Kumar Nigam, Kripabandhu Ghosh, Shouvik Kumar Guha, Arnab Bhattacharya, Ashutosh Modi
| Challenge: | a system that could assist a judge in predicting the outcome of a case should be explainable. |
| Approach: | They propose to use a corpus of 35k Indian Supreme Court cases annotated with original court decisions to promote research in this area. |
| Outcome: | The proposed system has an accuracy of 78% versus 94% for human legal experts. |
PEARL: Preference Extraction with Exemplar Augmentation and Retrieval with LLM Agents (2024.emnlp-industry)
Copied to clipboard
| Challenge: | Existing systems specialize in extracting customer preferences from standalone queries . absence of a conversational interface often leaves customers feeling the need for humanlike assistance . |
| Approach: | They propose a shopping assistant chatbot that extracts customer preferences as key-value filters from a multi-turn conversation on an e-commerce website. |
| Outcome: | The proposed solution improves performance on exact match by 10% compared to baselines and improves inference latency by 1%. |
Adv-OLM: Generating Textual Adversaries via OLM (2021.eacl-main)
Copied to clipboard
| Challenge: | Recent studies have pointed out the vulnerability of deep learning models to adversarial attacks. |
| Approach: | They propose a black-box attack method that adapts the idea of Occlusion and Language Models to the current state of the art attack methods. |
| Outcome: | The proposed method outperforms existing methods on several text classification tasks. |
CorrSynth - A Correlated Sampling Method for Diverse Dataset Generation from LLMs (2024.emnlp-main)
Copied to clipboard
| Challenge: | Large language models (LLMs) have demonstrated remarkable performance in diverse tasks using zero-shot and few-shot prompting. |
| Approach: | They propose a method which generates data that is more diverse and faithful to the input prompt using a correlated sampling strategy. |
| Outcome: | The proposed method overcomes the complexity drawbacks of other guidance-based techniques and improves student metrics and intrinsic metrics upon competitive baselines across four datasets. |
Socially Aware Bias Measurements for Hindi Language Representations (2022.naacl-main)
Copied to clipboard
| Challenge: | Language representations are an efficient tool used across NLP, but they are strife with encoded societal biases. |
| Approach: | They investigate the encoded biases in Hindi language representations based on cultural and historical contexts . they emphasize the necessity of social-awareness along with linguistic and grammatical artefacts when modeling language representation . |
| Outcome: | The proposed model reflects the cultural and cultural diversity of the region in which it is used . the model is based on the language and culture of the language being used based upon the study . |