Papers by Junlong Tong

3 papers
LLM as Effective Streaming Processor: Bridging Streaming-Batch Mismatches with Group Position Encoding (2025.findings-acl)

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Challenge: Existing methods for adapting LLMs to streaming rely on expensive re-encoding or limited scalability.
Approach: They propose a group position encoding paradigm built on batch architectures to enhance consistency between streaming and batch modes.
Outcome: The proposed method outperforms existing methods on cross-lingual and cross-modal tasks.
VisiPruner: Decoding Discontinuous Cross-Modal Dynamics for Efficient Multimodal LLMs (2025.emnlp-main)

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Challenge: Multimodal Large Language Models (MLLMs) suffer from significant computational overhead due to the quadratic growth of attention computations with the number of multimodal tokens.
Approach: They propose a training-free pruning framework that prunes multimodal tokens without a trained pruning method.
Outcome: The proposed pruning framework outperforms existing token pruning methods and generalizes across diverse MLLMs.
From Static Inference to Dynamic Interaction: A Survey of Streaming Large Language Models (2026.findings-acl)

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Challenge: Existing definitions of streaming LLMs are fragmented and lack a systematic taxonomy . large language models are pre-trained on static and full-context corpora .
Approach: They propose a systematic taxonomy of current streaming Large Language Models and propose underlying methodologies for streaming LLMs.
Outcome: The proposed model is based on data flow and dynamic interaction to clarify existing ambiguities.

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