3 papers
cs.LG2026
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…
cs.CL2025
Where is the signal in tokenization space?
Renato Lui Geh, Honghua Zhang, Kareem Ahmed +2
Large Language Models (LLMs) are typically shipped with tokenizers that deterministically encode text into so-called canonical token sequences, to which the LLMs assign probability…
cs.CL2025
Adversarial Tokenization
Renato Lui Geh, Zilei Shao, Guy Van den Broeck
Current LLM pipelines account for only one possible tokenization for a given string, ignoring exponentially many alternative tokenizations during training and inference. For exampl…