Papers by Disha Jindal
BIG-Bench Extra Hard (2025.acl-long)
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Mehran Kazemi, Bahare Fatemi, Hritik Bansal, John Palowitch, Chrysovalantis Anastasiou, Sanket Vaibhav Mehta, Lalit K Jain, Virginia Aglietti, Disha Jindal, Peter Chen, Nishanth Dikkala, Gladys Tyen, Xin Liu, Uri Shalit, Silvia Chiappa, Kate Olszewska, Yi Tay, Vinh Q. Tran, Quoc V Le, Orhan Firat
| Challenge: | Current benchmarks for large language model reasoning focus on math and coding abilities, leaving a gap in evaluating broader reasoning proficiencies. |
| Approach: | They propose a benchmark to evaluate general reasoning in large language models . they use BIG-Bench and its harder version BIG-Benefit Hard to assess general reasoning . |
| Outcome: | The new benchmark pushes the boundaries of LLM reasoning evaluation. |
Is Killed More Significant than Fled? A Contextual Model for Salient Event Detection (2020.coling-main)
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| Challenge: | Existing work on identifying the salient information in a text has used a limited representation of events that omits essential information. |
| Approach: | They propose a highly contextual model of event salience that uses a rich representation of events and integrates document-level information. |
| Outcome: | The proposed model improves on an event salience dataset by 2-4% on standard metrics and addresses flaws in existing evaluation methodologies. |