Papers by Zhihong Lei
Neural Language Modeling for Named Entity Recognition (2020.coling-main)
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| Challenge: | Experimental results show that named entity recognition systems are faster and more flexible for the size of the corpus. |
| Approach: | They propose to use a neural language model as an alternative to the conditional random field layer for named entity recognition. |
| Outcome: | The proposed system has a significant speed advantage with a marginal performance degradation. |
Math-Shepherd: Verify and Reinforce LLMs Step-by-step without Human Annotations (2024.acl-long)
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| Challenge: | Existing methods for process-oriented math reward models rely on manual annotation. |
| Approach: | They propose a process-oriented math process reward model called Math-shepherd which assigns a reward score to each step of math problem solutions. |
| Outcome: | The proposed model breaks the bottleneck of manual supervision in two scenarios. |