Papers by Pranav Shetty
“What is the value of templates?” Rethinking Document Information Extraction Datasets for LLMs (2024.findings-emnlp)
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Ran Zmigrod, Pranav Shetty, Mathieu Sibue, Zhiqiang Ma, Armineh Nourbakhsh, Xiaomo Liu, Manuela Veloso
| Challenge: | Existing work on prompt-response datasets for visually rich document understanding (VRDU) is labor-intensive. |
| Approach: | They propose a set of questions that are transformed from a key information extraction template to a prompt-response format using a plethora of bespoke templates. |
| Outcome: | The proposed datasets are compared with baseline models on K2Q with zero-shot prompting. |
ExStrucTiny: A Benchmark for Schema-Variable Structured Information Extraction from Document Images (2026.eacl-long)
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Mathieu Sibue, Andrés Muñoz Garza, Samuel Mensah, Pranav Shetty, Zhiqiang Ma, Xiaomo Liu, Manuela Veloso
| Challenge: | Existing models for structured information extraction are limited by narrow entity ontologies, simple queries, or homogeneous document types. |
| Approach: | They propose a benchmark dataset for structured Information Extraction (IE) from document images . they analyze open and closed VLMs on this benchmark . |
| Outcome: | The proposed model can perform fine-grained structured extraction across document types and schemas. |
CoCoLex: Confidence-guided Copy-based Decoding for Grounded Legal Text Generation (2025.acl-long)
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Santosh T.y.s.s, Youssef Tarek Elkhayat, Oana Ichim, Pranav Shetty, Dongsheng Wang, Zhiqiang Ma, Armineh Nourbakhsh, Xiaomo Liu
| Challenge: | LLMs can provide key benefits to the Legal domain, but their adoption has been hindered by their tendency to generate unfaithful, ungrounded, or hallucinatory outputs. |
| Approach: | They propose a Confidence-guided copy-based decoding strategy that dynamically interpolates the model produced vocabulary distribution with a distribution derived based on copying from the context. |
| Outcome: | The proposed method outperforms existing context-aware decoding methods on five legal benchmarks. |
BERTifying the Hidden Markov Model for Multi-Source Weakly Supervised Named Entity Recognition (2021.acl-long)
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| Challenge: | Existing NER models are supervised by a large number of training sequences, each pre-annotated with token-level labels. |
| Approach: | They propose a conditional hidden Markov model which can effectively infer true labels from multi-source noisy labels in an unsupervised way. |
| Outcome: | The proposed model outperforms state-of-the-art weakly supervised NER models on four benchmarks from various domains. |
Where is this coming from? Making groundedness count in the evaluation of Document VQA models (2025.findings-naacl)
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| Challenge: | Document Visual Question Answering (VQA) models have come close to or matching human performance on some benchmarks. |
| Approach: | They propose a method that accounts for the semantic and multimodal groundedness of a model’s outputs and can be parameterized so that users can configure the score according to their preferences. |
| Outcome: | The proposed method produces scores that are a better indicator of a model’s robustness and tends to give higher rewards to better-calibrated answers. |
Prompt-Based Rule Discovery and Boosting for Interactive Weakly-Supervised Learning (2022.acl-long)
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| Challenge: | Weakly-supervised learning (WSL) has shown promising results in addressing label scarcity on many NLP tasks, but manual designing a comprehensive, high-quality set of labeling rules is tedious and difficult. |
| Approach: | They propose a weakly-supervised learning model that iterates and discovers new labeling rules from data to improve the WSL model. |
| Outcome: | The proposed model outperforms state-of-the-art models on four tasks and bridges the gaps with fully supervised models. |
POLYIE: A Dataset of Information Extraction from Polymer Material Scientific Literature (2024.naacl-long)
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Jerry Cheung, Yuchen Zhuang, Yinghao Li, Pranav Shetty, Wantian Zhao, Sanjeev Grampurohit, Rampi Ramprasad, Chao Zhang
| Challenge: | SciIE datasets for polymer materials are lacking for this class of materials . POLYIE is curated from 146 full-length polymer scholarly articles . |
| Approach: | They propose a SciIE dataset for polymer materials that uses entity annotations from 146 full-length articles. |
| Outcome: | The proposed dataset is curated from 146 full-length polymer scholarly articles . it presents challenges due to diverse lexical formats of entities and ambiguity between entities . |
Detecting Non-Membership in LLM Training Data via Rank Correlations (2026.eacl-long)
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| Challenge: | Large language models (LLMs) are trained on increasingly vast and opaque text corpora. |
| Approach: | They propose a test that detects dataset-level non-membership using only grey-box access to model logits. |
| Outcome: | The proposed test detects dataset-level non-membership using only grey-box access to model logits. |