Papers by Zhanyu Shen

3 papers
LDIR: Low-Dimensional Dense and Interpretable Text Embeddings with Relative Representations (2025.findings-acl)

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Challenge: Existing text embeddings with high dimensions are difficult to trace and interpret.
Approach: They propose low-dimensional and interpretable text embeddings with relative representations that encode semantic meanings in a vector space where similar texts are close together in the representation space.
Outcome: The proposed embeddings outperform existing models on multiple tasks with fewer dimensions and are lowdimensional and dense while maintaining interpretability.
Evaluating Memory Capability in Continuous Lifelog Scenario (2026.findings-acl)

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Challenge: Existing benchmarks focus on online one-on-one chatting or human-AI interactions, neglecting real-world scenarios.
Approach: They propose a framework to curate a lifelog benchmark that combines two subsets of audio data to address temporal leakage in offline settings.
Outcome: The proposed framework outperforms existing benchmarks on live chats and AI interactions.
AnchorMem: Anchored Facts with Associative Contexts for Building Memory in Large Language Models (2026.findings-acl)

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Challenge: Existing memory systems rely on summarization to preserve contextual nuances and obscuring key retrieval features.
Approach: They propose a method that decouples the retrieval unit from the generation context.
Outcome: The proposed method outperforms baseline models on the LoCoMo benchmark.

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