Multi-lingual Evaluation of Code Generation Models (2022 · 86 citations)
Execution-based benchmarks for code generation, which run generated functions against unit tests, existed mostly for Python because hand-writing reliable tests is costly.
Domain-Specific Data Generation Framework for RAG Adaptation (2026)
Off-the-shelf RAG pipelines often perform poorly in specialised domains. Adapting their components, such as the embedding model or the generator LLM, requires domain-grounded training data, which is rarely available. The authors present RAGen, a data-centric framework that turns raw domain documents into…
Lunar-Bench: Towards Evaluating Task-Oriented Reasoning of LLMs in Lunar Exploration Scenarios (2026)
Large language models are increasingly proposed as assistants for lunar missions, but standard benchmarks test isolated, static questions.
Parallel-SFT: Improving Zero-Shot Cross-Programming-Language Transfer for Code RL (2026)
LLMs write code well in popular programming languages, but weaker data coverage hurts them in less common ones.
TIGER: Text-Informed Generalized Enzyme-Reaction Retrieval (2026)
TIGER addresses enzyme–reaction retrieval, a two-way matching task: given an enzyme, find the reactions it catalyzes, and given a reaction, find enzymes that could perform it.

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Papers of our library cite their works 59 times (of the 149,439 papers whose bibliographies we read); 15 citing papers with a page here →.

Updated 2 November 2026