Papers by Abhinav Rastogi
A Unified Approach to Entity-Centric Context Tracking in Social Conversations (2022.lrec-1)
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| Challenge: | Context Tracking is a computational task for human-human conversations . it involves identifying important entities and keeping track of their properties and relationships . |
| Approach: | They propose to use a human-human conversation corpus for context tracking with people and location annotations to model the conversation's context. |
| Outcome: | The proposed model is based on a large human-human conversation corpus with people and location annotations. |
MoDE: Effective Multi-task Parameter Efficient Fine-Tuning with a Mixture of Dyadic Experts (2025.findings-naacl)
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| Challenge: | Recent efforts have explored mixtures of LoRA modules for multi-task settings, but this study reveals redundancy in the down-projection matrix of these architectures. |
| Approach: | They propose a method to share down-projection matrix across tasks and employ atomic rank-one adapters coupled with routers that allow more sophisticated task-level specialization. |
| Outcome: | The proposed method outperforms state-of-the-art models on a SNI benchmark and provides a practical solution for deploying lightweight models. |
Show, Don’t Tell: Demonstrations Outperform Descriptions for Schema-Guided Task-Oriented Dialogue (2022.naacl-main)
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| Challenge: | Recent work has leveraged natural language descriptions of schema elements to enable universal dialogue systems; however, descriptions only indirectly convey schema semantics. |
| Approach: | They propose to use schema-guided modeling to prompt seq2seq models with a labeled example dialogue to show schema semantics rather than tell them. |
| Outcome: | The proposed model outperforms models using short examples as schema representations on two popular dialogue state tracking benchmarks. |
Template Guided Text Generation for Task-Oriented Dialogue (2020.emnlp-main)
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| Challenge: | a new study examines the use of templates to generate natural language utterances for a large number of APIs. |
| Approach: | They propose a schema-guided approach which conditions the generation on a natural language schema. |
| Outcome: | The proposed method improves over strong baselines, is robust to out-of-domain inputs and shows improved sample efficiency. |
Efficient Entity Embedding Construction from Type Knowledge for BERT (2022.findings-aacl)
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| Challenge: | Existing work has shown advantages of incorporating knowledge graphs (KGs) into BERT for various NLP tasks. |
| Approach: | They propose to integrate knowledge graphs into BERT to train entity embeddings to include rich information of factual knowledge. |
| Outcome: | The proposed models perform very well when combined with context. |
AnyTOD: A Programmable Task-Oriented Dialog System (2023.emnlp-main)
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Jeffrey Zhao, Yuan Cao, Raghav Gupta, Harrison Lee, Abhinav Rastogi, Mingqiu Wang, Hagen Soltau, Izhak Shafran, Yonghui Wu
| Challenge: | a neuro-symbolic approach allows zero-shot adaptation to unseen tasks and domains . a neural LM keeps track of events that occur during a conversation and a symbolic program implements dialog policy is executed to recommend actions. |
| Approach: | They propose an end-to-end, zero-shot task-oriented dialog system . it is designed to adapt to unseen tasks or domains without prior training . |
| Outcome: | The proposed system can be programmed to adapt to unseen tasks without training . it reduces data collection and training requirements for enabling new TOD 1 16189 tasks . |