3 papers
cs.AI2026
Input-Conditioned Search for Efficient Test-Time Scaling of Recursive Reasoners
Haochen Shi, Tianwen Fu, Qianggang Ding +7
People often tackle difficult problems by thinking more deeply or exploring more possibilities. Similarly, recursive reasoners, which reason by repeatedly applying a learned update…
cs.CL2026
Simplifying the Modeling of Arbitrary Conditionals in Natural Language
Yinhan Lu, Eric Elmoznino, Léo Gagnon +3
Causal Transformers model sequences through an autoregressive factorization of the joint distribution, which enables efficient left-to-right decoding and conditional likelihood com…
cs.CL2026
An Empirical Study of Many-Shot In-Context Learning for Machine Translation of Low-Resource Languages
Yinhan Lu, Gaganpreet Jhajj, Chen Zhang +2
In-context learning (ICL) allows large language models (LLMs) to adapt to new tasks from a few examples, making it promising for languages underrepresented in pre-training. Recent…