Papers by Shagun Sodhani
CLUTRR: A Diagnostic Benchmark for Inductive Reasoning from Text (D19-1)
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| Challenge: | Existing datasets for reading comprehension tasks have been used to test the generalization of natural language understanding systems. |
| Approach: | They propose a diagnostic benchmark suite to clarify key issues related to the robustness and systematicity of NLU systems. |
| Outcome: | The proposed benchmark suite clarifies key issues related to the robustness and systematicity of NLU systems. |
Do Large Language Models Know How Much They Know? (2024.emnlp-main)
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| Challenge: | Large Language Models are highly capable systems, but their capabilities and limitations are unclear. |
| Approach: | They develop a benchmark that challenges LLMs to recall all information they possess on specific topics. |
| Outcome: | The proposed model can recall excessive, insufficient, or the precise amount of information they possess on a given topic, indicating their awareness of how much they know about the given topic. |
EpiK-Eval: Evaluation for Language Models as Epistemic Models (2023.emnlp-main)
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| Challenge: | Developing systems that can reason through language understanding has been a cornerstone in natural language processing research. |
| Approach: | They propose a question-answering benchmark to evaluate LLMs' ability to combine knowledge from different training documents within their parameter space. |
| Outcome: | The proposed benchmark aims to evaluate LLMs' ability to combine knowledge from different training documents within their parameter space. |