5 papers
Beyond Real: Imaginary Extension of Rotary Position Embeddings for Long-Context LLMs
Xiaoran Liu, Yuerong Song, Zhigeng Liu +6
Rotary Position Embeddings (RoPE) have become a standard for encoding sequence order in Large Language Models (LLMs) by applying rotations to query and key vectors in the complex p…
Sparse-dLLM: Accelerating Diffusion LLMs with Dynamic Cache Eviction
Yuerong Song, Xiaoran Liu, Ruixiao Li +5
Diffusion Large Language Models (dLLMs) enable breakthroughs in reasoning and parallel decoding but suffer from prohibitive quadratic computational complexity and memory overhead d…
Beyond Homogeneous Attention: Memory-Efficient LLMs via Fourier-Approximated KV Cache
Xiaoran Liu, Siyang He, Qiqi Wang +9
Large Language Models struggle with memory demands from the growing Key-Value (KV) cache as context lengths increase. Existing compression methods homogenize head dimensions or rel…
LongLLaDA: Unlocking Long Context Capabilities in Diffusion LLMs
Xiaoran Liu, Yuerong Song, Zhigeng Liu +4
Large Language Diffusion Models, or diffusion LLMs, have emerged as a significant focus in NLP research, with substantial effort directed toward understanding their scalability and…
Thus Spake Long-Context Large Language Model
Xiaoran Liu, Ruixiao Li, Mianqiu Huang +11
Long context is an important topic in Natural Language Processing (NLP), running through the development of NLP architectures, and offers immense opportunities for Large Language M…