Papers by Taehee Kim
Cluster-Guided Label Generation in Extreme Multi-Label Classification (2023.eacl-main)
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| Challenge: | Existing classification-based models are poorly per-form for tail labels and ignore semantic relations among labels. |
| Approach: | They propose to guide label generation using label cluster information to hierarchically generate lower-level labels. |
| Outcome: | The proposed model outperforms classification and generation baselines on tail labels and improves in four popular XMC benchmarks. |
When Thoughts Meet Facts: Reusable Reasoning for Long-Context LMs (2026.findings-acl)
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| Challenge: | Recent Long-Context Language Models (LCLMs) do not capture how evidence should be connected . a new framework that integrates thought templates into LCLM frameworks is proving useful . |
| Approach: | They propose a framework that iteratively refines reusable reasoning patterns derived from prior problem solving to improve their templates. |
| Outcome: | The proposed framework outperforms baselines on knowledge-intensive multi-hop reasoning benchmarks and practical scenarios without retrieval. |
PePe: Personalized Post-editing Model utilizing User-generated Post-edits (2023.findings-eacl)
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| Challenge: | Existing neural machine translation models ignore personal style in their translations, but in these studies the definition of personal style is over-simplified. |
| Approach: | They propose a personalized automatic post-editing framework that generates sentences considering distinct personal behaviors by collecting post-edited data from a live machine translation system and combining a discriminator module and user-specific parameters. |
| Outcome: | The proposed model outperforms baseline models on four different metrics including BLEU, TER, YiSi-1, and human evaluation. |
Retrieve Only Relevant Tables Whether Few or Many: Adaptive Table Retrieval Method (2026.findings-acl)
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| Challenge: | Existing methods for retrieving relevant tables from databases are limited by the number of tables required. |
| Approach: | They propose an adaptive table retrieval method that adjusts the number of tables retrieved according to the requirements of each query. |
| Outcome: | Experiments on Spider, BIRD, and Spider 2.0 show that the proposed method improves performance and retrieval and downstream tasks. |
Polishing Every Facet of the GEM: Testing Linguistic Competence of LLMs and Humans in Korean (2025.acl-long)
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| Challenge: | Existing studies have focused on linguistic competence of language models with grammatical knowledge. |
| Approach: | They propose to use grammar as a measurable proxy to assess linguistic competence of large language models (LLMs) . |
| Outcome: | The proposed model aims to assess the linguistic competence of large language models (LLMs) and humans in Korean. |