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cs.CL2024
Deliberation in Latent Space via Differentiable Cache Augmentation
Luyang Liu, Jonas Pfeiffer, Jiaxing Wu +2
Techniques enabling large language models (LLMs) to "think more" by generating and attending to intermediate reasoning steps have shown promise in solving complex problems. However…
cs.CL2024
RLPF: Reinforcement Learning from Prediction Feedback for User Summarization with LLMs
Jiaxing Wu, Lin Ning, Luyang Liu +7
LLM-powered personalization agent systems employ Large Language Models (LLMs) to predict users' behavior from their past activities. However, their effectiveness often hinges on th…
cs.CL2024
User-LLM: Efficient LLM Contextualization with User Embeddings
Lin Ning, Luyang Liu, Jiaxing Wu +6
Large language models (LLMs) have achieved remarkable success across various domains, but effectively incorporating complex and potentially noisy user timeline data into LLMs remai…