Papers by Siva Patel
doc2dial: A Goal-Oriented Document-Grounded Dialogue Dataset (2020.emnlp-main)
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| Challenge: | doc2dial dataset is a goal-oriented document-grounded dialogue model . it is based on how the authors compose documents for guiding end users . |
| Approach: | They propose a dataset of goal-oriented dialogues grounded in documents . they use annotated conversations with an average of 14 turns to generate conversational utterances . |
| Outcome: | The proposed dataset includes over 4500 annotated conversations with an average of 14 turns grounded in over 450 documents from four domains. |
MAGNIFICo: Evaluating the In-Context Learning Ability of Large Language Models to Generalize to Novel Interpretations (2023.emnlp-main)
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| Challenge: | Large Language Models (LLMs) have a knowledge cutoff and are costly to finetune repeatedly. |
| Approach: | They introduce a language evaluation suite that incorporates diverse tokens and prompt settings to simulate real-world complexity. |
| Outcome: | The proposed evaluation suite incorporates diverse tokens and prompt settings to simulate real-world complexity. |
Agent Assist through Conversation Analysis (2020.emnlp-demos)
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Kshitij Fadnis, Nathaniel Mills, Jatin Ganhotra, Haggai Roitman, Gaurav Pandey, Doron Cohen, Yosi Mass, Shai Erera, Chulaka Gunasekara, Danish Contractor, Siva Patel, Q. Vera Liao, Sachindra Joshi, Luis Lastras, David Konopnicki
| Challenge: | Using conversational approach to information retrieval for agent assistance, customer support agents are a critical part of an organization's customer support team. |
| Approach: | They propose a conversational approach to information retrieval for agent assistance that monitors an evolving conversation and recommends both responses and URLs of documents. |
| Outcome: | The proposed system monitors an evolving conversation and recommends both responses and URLs of documents the agent can use in replies to their client. |
Semi-Structured Object Sequence Encoders (2023.findings-emnlp)
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Rudra Murthy, Riyaz Bhat, Chulaka Gunasekara, Siva Patel, Hui Wan, Tejas Dhamecha, Danish Contractor, Marina Danilevsky
| Challenge: | Semi-structured object sequences are often represented as a sequence of key-value pairs over time . authors propose a two-part approach that takes each key independently and encodes a representation of its values over time. |
| Approach: | They propose a two-part approach that first considers each key independently and encodes a representation of its values over time. |
| Outcome: | The proposed approach outperforms existing methods on multiple prediction tasks using real-world data. |
Evaluating In-Context Learning of Libraries for Code Generation (2024.naacl-long)
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| Challenge: | Recent work shows that large proprietary LLMs can learn novel library usage in-context from demonstrations. |
| Approach: | They evaluate large proprietary LLMs to understand library usage in-context . they find they are able to generate code based on library specification presented in-constext - a promising area . |
| Outcome: | The proposed models can learn library usage in-context from demonstrations . the results pave the way for more adaptable and dynamic coding environments. |