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Sciriff: A resource to enhance language model instruction-following over scientific literature
We present SciRIFF (Scientific Resource for Instruction-Following and Finetuning), a dataset
of 137K instruction-following demonstrations for 54 tasks covering five essential scientific …
of 137K instruction-following demonstrations for 54 tasks covering five essential scientific …
Meta-reasoning: Semantics-symbol deconstruction for large language models
Neural-symbolic methods have demonstrated efficiency in enhancing the reasoning abilities
of large language models (LLMs). However, existing methods mainly rely on syntactically …
of large language models (LLMs). However, existing methods mainly rely on syntactically …
EXCGEC: A Benchmark of Edit-wise Explainable Chinese Grammatical Error Correction
Existing studies explore the explainability of Grammatical Error Correction (GEC) in a limited
scenario, where they ignore the interaction between corrections and explanations. To bridge …
scenario, where they ignore the interaction between corrections and explanations. To bridge …
SWE-Fixer: Training Open-Source LLMs for Effective and Efficient GitHub Issue Resolution
Large Language Models (LLMs) have demonstrated remarkable proficiency across a variety
of complex tasks. One significant application of LLMs is in tackling software engineering …
of complex tasks. One significant application of LLMs is in tackling software engineering …
eC-Tab2Text: Aspect-Based Text Generation from e-Commerce Product Tables
LAG Guanilo, MT Nayeem, C López… - arxiv preprint arxiv …, 2025 - arxiv.org
Large Language Models (LLMs) have demonstrated exceptional versatility across diverse
domains, yet their application in e-commerce remains underexplored due to a lack of …
domains, yet their application in e-commerce remains underexplored due to a lack of …