Small language models: Survey, measurements, and insights
Small language models (SLMs), despite their widespread adoption in modern smart
devices, have received significantly less academic attention compared to their large …
devices, have received significantly less academic attention compared to their large …
Emma-500: Enhancing massively multilingual adaptation of large language models
In this work, we introduce EMMA-500, a large-scale multilingual language model continue-
trained on texts across 546 languages designed for enhanced multilingual performance …
trained on texts across 546 languages designed for enhanced multilingual performance …
FRoG: Evaluating Fuzzy Reasoning of Generalized Quantifiers in LLMs
Fuzzy reasoning is vital due to the frequent use of imprecise information in daily contexts.
However, the ability of current large language models (LLMs) to handle such reasoning …
However, the ability of current large language models (LLMs) to handle such reasoning …
CodePMP: Scalable Preference Model Pretraining for Large Language Model Reasoning
Large language models (LLMs) have made significant progress in natural language
understanding and generation, driven by scalable pretraining and advanced finetuning …
understanding and generation, driven by scalable pretraining and advanced finetuning …
:Revealing the Decisive Effect of Instruction Diversity on Generalization
Understanding and accurately following instructions is critical for large language models
(LLMs) to be effective across diverse tasks. In this work, we rigorously examine the key …
(LLMs) to be effective across diverse tasks. In this work, we rigorously examine the key …
Thinking with Knowledge Graphs: Enhancing LLM Reasoning Through Structured Data
Large Language Models (LLMs) have demonstrated remarkable capabilities in natural
language understanding and generation. However, they often struggle with complex …
language understanding and generation. However, they often struggle with complex …