3 papers
cs.CL2026
Source-Grounded Semantic Reinforcement Learning for Low-Resource Target-Language Generation
Zeli Su, Ziyin Zhang, Zewei Pan +8
Low-resource target-language generation is often limited by scarce parallel data, while high-resource source-language monolingual data is abundant but difficult to use with standar…
cs.AI2026
TRACER: Turn-level Regret Matching with Inner Reinforcement Credit for Cooperative Multi-LLM Reasoning
Chusen Li, Zhou Liu, Shuigeng Zhou +1
Large language models increasingly rely on either reinforcement learning or multi-agent prompting to improve reasoning, yet these two paradigms remain difficult to combine. Directl…
q-bio.QM2026
Decoding Translation-Related Functional Sequences in 5'UTRs Using Interpretable Deep Learning Models
Yuxi Lin, Yaxue Fang, Zehong Zhang +4
Understanding how 5' untranslated regions (5'UTRs) regulate mRNA translation is critical for controlling protein expression and designing effective therapeutic mRNAs. While recent…