4 papers · 1 filter
Planned Diffusion
Daniel Israel, Tian Jin, Ellie Cheng +4
Most large language models are autoregressive: they generate tokens one at a time. Discrete diffusion language models can generate multiple tokens in parallel, but sampling from th…
The Pitfalls of KV Cache Compression
Alex Chen, Renato Geh, Aditya Grover +2
KV cache compression promises increased throughput and efficiency with negligible loss in performance. While the gains in throughput are indisputable and recent literature has inde…
Accelerating Diffusion LLMs via Adaptive Parallel Decoding
Daniel Israel, Guy Van den Broeck, Aditya Grover
The generation speed of LLMs are bottlenecked by autoregressive decoding, where tokens are predicted sequentially one by one. Alternatively, diffusion large language models (dLLMs)…
Enabling Autoregressive Models to Fill In Masked Tokens
Daniel Israel, Aditya Grover, Guy Van den Broeck
Historically, LLMs have been trained using either autoregressive (AR) or masked language modeling (MLM) objectives, with AR models gaining dominance in recent years. However, AR mo…