Papers by Yandong Chen

2 papers
Don’t Reinvent the Wheel: Efficient Instruction-Following Text Embedding based on Guided Space Transformation (2025.acl-long)

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Challenge: Existing methods for text embedding require re-encoding the entire corpus for each instruction.
Approach: They propose a framework that generates dynamic text embeddings that adapt to user instructions, highlighting specific attributes of text.
Outcome: The proposed framework improves instruction-following text embedding quality over state-of-the-art methods while speeding up processing on large datasets.
RouterEval: A Comprehensive Benchmark for Routing LLMs to Explore Model-level Scaling Up in LLMs (2025.findings-emnlp)

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Challenge: a lack of comprehensive benchmarks for Routing large language models has hindered the development of routers.
Approach: They propose a router-based benchmark to evaluate Routing large language models . the benchmark includes performance records for 12 popular LLM evaluations .
Outcome: The proposed model-level scaling up phenomenon can surpass the best single model in the pool and many existing strong LLMs.

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