37 citations · 154 across the 22 of their papers we have counts for
3 papers · 1 filter
Do Retrieval Augmented Language Models Know When They Don't Know?
Youchao Zhou, Heyan Huang, Yicheng Liu +5
Existing large language models (LLMs) occasionally generate plausible yet factually incorrect responses, known as hallucinations. Two main approaches have been proposed to mitigate…
SampleAttention: Near-Lossless Acceleration of Long Context LLM Inference with Adaptive Structured Sparse Attention
Qianchao Zhu, Jiangfei Duan, Chang Chen +6
Large language models (LLMs) now support extremely long context windows, but the quadratic complexity of vanilla attention results in significantly long Time-to-First-Token (TTFT)…
InternLM2 Technical Report
Zheng Cai, Maosong Cao, Haojiong Chen +97
The evolution of Large Language Models (LLMs) like ChatGPT and GPT-4 has sparked discussions on the advent of Artificial General Intelligence (AGI). However, replicating such advan…