Papers by Wayne Zhang

3 papers
Session-level Language Modeling for Conversational Speech (D18-1)

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Challenge: Xiong et al., 2017) generalizes language models for conversational speech recognition . recurrent neural networks (RNNs) read a list of words sequentially and predict the next word at each position.
Approach: They propose to generalize language models for conversational speech recognition to capture conversation-level phenomena such as adjacency pairs, lexical entrainment, and topical coherence.
Outcome: The proposed model reduces perplexity and improves word error rate over standard models in the conversational telephone speech domain.
LLM-Friendly Knowledge Representation for Customer Support (2025.coling-industry)

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Challenge: a new approach to customer support is proposed to integrate large language models with a framework designed to navigate the complexities of Airbnb customer support operations.
Approach: They propose a method for integrating Large Language Models with a framework designed to navigate the complexities of Airbnb customer support operations.
Outcome: The proposed approach is cost-effective and improves customer support performance . it also allows human agents to focus on more complex issues, the authors show .
RelayAttention for Efficient Large Language Model Serving with Long System Prompts (2024.acl-long)

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Challenge: a long system prompt causes throughput/latency bottlenecks as the cost of generating the next token increases w.r.t the sequence length.
Approach: They propose an attention algorithm that reads hidden state from DRAM exactly once for a batch of input tokens.
Outcome: The proposed algorithm reduces the need for redundant memory accesses in existing algorithms.

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