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Tan Yi-Chern

2 accepted papers

2026

Learning is Forgetting; LLM Training As Lossy Compression

ICLR 2026poster

Despite the increasing prevalence of large language models (LLMs), we still have a limited understanding of how their representational spaces are structured. This limits our ability to interpret how and what they learn or relate them to learning in humans. We argue LLMs are best seen as an instance…

Cited by 0SourcecodeScholar
2025

No Need for Explanations: LLMs can implicitly learn from mistakes in-context

EMNLP 2025

Showing incorrect answers to Large Language Models (LLMs) is a popular strategy to improve their performance in reasoning-intensive tasks. It is widely assumed that, in order to be helpful, the incorrect answers must be accompanied by comprehensive rationales, explicitly detailing where the mistakes

Cited by 0SourcePDFScholar