32 citations · 80 across the 32 of their papers we have counts for
14 papers · 1 filter
ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects
Jipeng Zhang, Haolin Yang, Kehao Miao +4
Recent text-to-SQL models have achieved strong performance, but their effectiveness remains largely confined to SQLite due to dataset limitations. However, real-world applications…
MA-LoT: Model-Collaboration Lean-based Long Chain-of-Thought Reasoning enhances Formal Theorem Proving
Ruida Wang, Rui Pan, Yuxin Li +6
Solving mathematical problems using computer-verifiable languages like Lean has significantly impacted the mathematical and computer science communities. State-of-the-art methods u…
Fox-1: Open Small Language Model for Cloud and Edge
Zijian Hu, Jipeng Zhang, Rui Pan +9
We present Fox-1, a series of small language models (SLMs) consisting of Fox-1-1.6B and Fox-1-1.6B-Instruct-v0.1. These models are pre-trained on 3 trillion tokens of web-scraped d…
Bridge-Coder: Unlocking LLMs' Potential to Overcome Language Gaps in Low-Resource Code
Jipeng Zhang, Jianshu Zhang, Yuanzhe Li +5
Large Language Models (LLMs) demonstrate strong proficiency in generating code for high-resource programming languages (HRPLs) like Python but struggle significantly with low-resou…
FIRST: Teach A Reliable Large Language Model Through Efficient Trustworthy Distillation
KaShun Shum, Minrui Xu, Jianshu Zhang +5
Large language models (LLMs) have become increasingly prevalent in our daily lives, leading to an expectation for LLMs to be trustworthy -- - both accurate and well-calibrated (the…
TAGCOS: Task-agnostic Gradient Clustered Coreset Selection for Instruction Tuning Data
Jipeng Zhang, Yaxuan Qin, Renjie Pi +3
Instruction tuning has achieved unprecedented success in NLP, turning large language models into versatile chatbots. However, the increasing variety and volume of instruction datas…