Papers by Yuanjun Shi
ReTRE: Benchmarking LLM Transfer Robustness with Structure-Preserving Variants (2026.acl-long)
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| Challenge: | Learning transfer theory emphasizes that applying acquired knowledge to novel manifestations is a key signal of deep understanding |
| Approach: | They propose a benchmark that probes transfer robustness along two rewrite levels: Near Transfer and Far Transfer. |
| Outcome: | The proposed benchmark demonstrates that large language models are robust when faced with novel manifestations of the same problem. |
Adaptive End-to-End Metric Learning for Zero-Shot Cross-Domain Slot Filling (2023.emnlp-main)
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| Challenge: | Recent research on slot filling has witnessed considerable improvement with considerable data and label shifts. |
| Approach: | They propose an adaptive end-to-end metric learning scheme for zero-shot slot filling that uses context-aware soft label representations and slot-level contrastive representation learning to mitigate the data and label shift problems. |
| Outcome: | The proposed approach outperforms existing methods on public benchmarks and shows that it is simple, efficient and generalizable. |