Papers by Muru Zhang
Measuring and Narrowing the Compositionality Gap in Language Models (2023.findings-emnlp)
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| Challenge: | a language model can correctly answer all sub-problems but not generate the overall solution. |
| Approach: | They propose a method that asks itself and then answers follow-up questions to narrow the compositionality gap by reasoning explicitly instead of implicitly. |
| Outcome: | The proposed method improves on chain of thought by asking itself and answering follow-up questions. |
Intriguing Effect of the Correlation Prior on ICD-9 Code Assignment (2023.acl-srw)
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| Challenge: | The Ninth Revision of the International Classification of Diseases (ICD-9) is a standardized coding system used worldwide to classify and code diseases, injuries, and other health conditions. |
| Approach: | They evaluate the usefulness of correlation bias and suggest it could improve ICD-9 code assignment in some cases. |
| Outcome: | The proposed model improves on classes that are more imbalanced and less correlated with other codes, but the effect on individual class can be negative or positive. |
Why Do Some Inputs Break Low-Bit LLM Quantization? (2025.emnlp-main)
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| Challenge: | Low-bit weight-only quantization reduces memory usage but disproportionately affects certain examples. |
| Approach: | They analyze quantization errors of 50 pairs of methods on large language models and test their hypothesis . |
| Outcome: | The proposed method reduces the memory footprint of large language models while maintaining reasonable performance across benchmarks. |