3 papers
cs.AI2026
When Summaries Distort Decisions: Information Fidelity in LLM-Compressed Financial Analysis
Hoyoung Lee, Suhwan Park, Seunghan Lee +15
Financial decision-makers face more information than they can directly inspect, making context compression necessary. Yet when large language models (LLMs) compress financial sourc…
cs.CL2026
When Multiple Scripts Matter: Evaluating ASR in Clinical Settings
Jean Seo, Minkyu Kim, Jeonguk Lee +3
Automatic speech recognition (ASR) in non-English clinical settings is challenged by multiscript variability, where the same term may appear in multiple valid orthographic forms. C…
cs.CE2026
From Text to Alpha: Can LLMs Track Evolving Signals in Corporate Disclosures?
Chanyeol Choi, Yoon Kim, Yu Yu +10
Natural language processing (NLP) has been widely used in quantitative finance, but traditional methods often struggle to capture rich narratives in corporate disclosures, leaving…