Papers by Palak Jain
DiffQG: Generating Questions to Summarize Factual Changes (2023.eacl-main)
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Jeremy R. Cole, Palak Jain, Julian Martin Eisenschlos, Michael J.Q. Zhang, Eunsol Choi, Bhuwan Dhingra
| Challenge: | Existing methods to identify factual changes between paired documents are limited . specialized entailment-like resources and models have been applied to fact verification . |
| Approach: | They propose to represent factual changes between paired documents as question-answer pairs . they propose to generate a discriminating question given an answer span such that the question is answerable by one passage but not the other . |
| Outcome: | The proposed model can flexibly and concisely capture the updated contents of paired documents. |
1-PAGER: One Pass Answer Generation and Evidence Retrieval (2023.findings-emnlp)
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| Challenge: | 1-Pager is the first system that answers a question and retrieves evidence using a single Transformer-based model and decoding process. |
| Approach: | They propose a system that partitions the corpus using constrained decoding to select a document and answer string, and a method that uses a single Transformer-based model to generate evidence. |
| Outcome: | The proposed system outperforms the equivalent ‘closed-book’ question answering model by grounding predictions in evidence corpus. |
From RAG to Riches: Retrieval Interlaced with Sequence Generation (2024.emnlp-main)
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| Challenge: | RICHES interleaves retrieval with sequence generation tasks . traditional approaches chain LLM generation with separate retrieval model . |
| Approach: | They propose a novel approach that interleaves retrieval with sequence generation tasks . they propose attributed evidence, multi-hop retrievals and interleave thoughts to plan on what to retrieve next . |
| Outcome: | The proposed approach can work with any Instruction-tuned model, without additional training. |