most citedAdvancing Speech Language Models by Scaling Supervised Fine-Tuning with Over 60,000 Hours of Synthetic Speech Dialogue Data

1 citations · 1 across the 2 of their papers we have counts for

collaborators

3 papers

cs.IR2025

InfoDeepSeek: Benchmarking Agentic Information Seeking for Retrieval-Augmented Generation

Yunjia Xi, Jianghao Lin, Menghui Zhu +10

Retrieval-Augmented Generation (RAG) enhances large language models (LLMs) by grounding responses with retrieved information. As an emerging paradigm, Agentic RAG further enhances…

cs.CL2024★ 1 cited

Advancing Speech Language Models by Scaling Supervised Fine-Tuning with Over 60,000 Hours of Synthetic Speech Dialogue Data

Shuaijiang Zhao, Tingwei Guo, Bajian Xiang +4

The GPT-4o represents a significant milestone in enabling real-time interaction with large language models (LLMs) through speech, its remarkable low latency and high fluency not on…

physics.ed-ph2024

Using Large Language Models to Assign Partial Credit to Students' Explanations of Problem-Solving Process: Grade at Human Level Accuracy with Grading Confidence Index and Personalized Student-facing Feedback

Zhongzhou Chen, Tong Wan

This study examines the feasibility and potential advantages of using large language models, in particular GPT-4o, to perform partial credit grading of large numbers of student wri…