Papers by Sijun Zhang

2 papers
LLoCO: Learning Long Contexts Offline (2024.emnlp-main)

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Challenge: Large language models are still unable to handle long contexts due to the quadratic computational and memory overhead of the self-attention mechanism and the substantial KV cache sizes during generation.
Approach: They propose a method to learn contexts offline through context compression and in-domain parameter-efficient finetuning with LoRA.
Outcome: The proposed model outperforms in-context learning while using 30 fewer tokens during inference and significantly reduces the cost of long document question answering.
Beyond Transcription: Unified Audio Schema for Perception-Aware AudioLLMs (2026.findings-acl)

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Challenge: Recent Audio Large Language Models (AudioLLMs) excel at reasoning tasks, but struggle at elementary auditory perception.
Approach: They propose a framework that organizes audio information into three explicit components in a unified JSON format.
Outcome: The proposed framework boosts fine-grained perception by 10.9% on MMSU over state-of-the-art models while preserving robust reasoning capabilities.

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