Papers with KCL-Essay

1 papers
Korean Canonical Legal Benchmark: Toward Knowledge-Independent Evaluation of LLMs’ Legal Reasoning Capabilities (2026.eacl-short)

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Challenge: Large reasoning models trained to reason explicitly in the verbal space have shown superior performance over general large language models (Guo et al., 2025).
Approach: They propose to use Korean Canonical Legal Benchmark to assess language models' legal reasoning capabilities independently of domain-specific knowledge.
Outcome: The proposed benchmark outperforms general-purpose models in a systematic evaluation of 30+ models.

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