Research author
Maxime Peyrard
2 AI research papers in the One9Founders library, with summaries and links to original sources.
Papers by Maxime Peyrard
Apr 21, 2026
cs.CL
What Makes an LLM a Good Optimizer? A Trajectory Analysis of LLM-Guided Evolutionary Search
Xinhao Zhang, Xi Chen, François Portet, et al.
3
Mar 19, 2026
cs.CL
What Really Controls Temporal Reasoning in Large Language Models: Tokenisation or Representation of Time?
Gagan Bhatia, Ahmad Muhammad Isa, Maxime Peyrard, et al.
This paper introduces MultiTempBench, a benchmark for testing how well large language models handle temporal reasoning (like date arithmetic and timezone conversion) across five languages and different calendar systems. The researchers discovered that how dates are broken into tokens (small text pieces) is crucial for low-resource languages, while high-resource languages rely more on learning temporal patterns, revealing that tokenization quality is a key bottleneck limiting AI's ability to reason about time.
temporal reasoningmultilingual NLPtokenizationbenchmarking
1