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Soumya Sharma

5 accepted papers

2026

Robust Reward Modeling via Causal Rubrics

ICLR 2026poster

Reward models (RMs) are fundamental to aligning Large Language Models (LLMs) via human feedback, yet they often suffer from reward hacking. They tend to latch on to superficial or spurious attributes, such as response length or formatting, mistaking these cues learned from correlations in training d…

Cited by 0SourceScholar
2023

Financial Numeric Extreme Labelling: A dataset and benchmarking

ACL 2023findings

The U.S. Securities and Exchange Commission (SEC) mandates all public companies to file periodic financial statements that should contain numerals annotated with a particular label from a taxonomy. In this paper, we formulate the task of automating the assignment of a label to a particular numeral s…

Cited by 7SourcePDFScholar
2022

ECTSum: A New Benchmark Dataset For Bullet Point Summarization of Long Earnings Call Transcripts

EMNLP 2022main

Despite tremendous progress in automatic summarization, state-of-the-art methods are predominantly trained to excel in summarizing short newswire articles, or documents with strong layout biases such as scientific articles or government reports. Efficient techniques to summarize financial documents,…

2022

Realistic Data Augmentation Framework for Enhancing Tabular Reasoning

EMNLP 2022finding

Existing approaches to constructing training data for Natural Language Inference (NLI) tasks, such as for semi-structured table reasoning, are either via crowdsourcing or fully automatic methods. However, the former is expensive and time consuming and thus limits scale, and the latter often produces…

Cited by 4SourcePDFScholar
2021

Question Answering over Electronic Devices: A New Benchmark Dataset and a Multi-Task Learning based QA Framework

EMNLP 2021finding

Answering questions asked from instructional corpora such as E-manuals, recipe books, etc., has been far less studied than open-domain factoid context-based question answering. This can be primarily attributed to the absence of standard benchmark datasets. In this paper, we meticulously create a lar…