Papers by Jan-Christoph Kalo
Evaluating the Knowledge Base Completion Potential of GPT (2023.findings-emnlp)
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| Challenge: | Language models (LMs) have been proposed for unsupervised knowledge base completion (KBC) however, their ability to do this at scale and with high accuracy remains an open question. |
| Approach: | They propose to use language models to complete a large public KB, Wikidata, with 90% precision. |
| Outcome: | The proposed models can extend Wikidata by 27M facts at 90% precision. |
ChronoSense: Exploring Temporal Understanding in Large Language Models with Time Intervals of Events (2025.acl-short)
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| Challenge: | Large Language Models (LLMs) still face significant challenges in reasoning and arithmetic. |
| Approach: | They propose a new benchmark to evaluate LLMs' temporal understanding that includes 16 tasks identifying the Allen relation between two temporal events and temporal arithmetic. |
| Outcome: | The proposed model handles Allen relations, even symmetrical ones, quite differently. |
Retrieval-based Question Answering with Passage Expansion Using a Knowledge Graph (2024.lrec-main)
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| Challenge: | Recent advances in dense neural retrievers and language models have hindered performance, especially for less common entities and facts. |
| Approach: | They propose a multi-modal passage retrieval model that combines entity features and textual data to improve retrieval precision for less common entities. |
| Outcome: | The proposed model improves retrieval precision on less common entities and facts on common benchmarks. |