4 papers
FourierSampler: Unlocking Non-Autoregressive Potential in Diffusion Language Models via Frequency-Guided Generation
Siyang He, Qiqi Wang, Xiaoran Liu +8
Despite the non-autoregressive potential of diffusion language models (dLLMs), existing decoding strategies demonstrate positional bias, failing to fully unlock the potential of ar…
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…
EvoSyn: Generalizable Evolutionary Data Synthesis for Verifiable Learning
He Du, Bowen Li, Aijun Yang +3
Reliable verifiable data has become a key driver of capability gains in modern language models, enabling stable reinforcement learning with verifiable rewards and effective distill…
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…