Papers by Keyu Mao
BiCSRouter: Bi-Level Cross-System Routing for Utility-Aware LLM Inference (2026.findings-acl)
Copied to clipboard
| Challenge: | Existing routing frameworks operate within a single computational paradigm . a cross-system routing framework that integrates two orthogonal regimes is proposed . |
| Approach: | They propose a cross-system routing framework that integrates two orthogonal regimes . they propose MBPP-based model that decomposes routing into intra-regime configuration selection and inter-regem system selection . |
| Outcome: | The proposed framework outperforms 15 representative baselines on MBPP and MATH benchmarks. |
Embedding-based In-Context Prompt Training for Enhancing LLMs as Text Encoders (2026.findings-acl)
Copied to clipboard
| Challenge: | Large language models (LLMs) have been widely explored for embedding generation. |
| Approach: | They propose an embedding-based in-context prompt training strategy that leverages in-constext learning to generate high-quality embeddables while reducing computational burden. |
| Outcome: | The proposed method surpasses models trained on publicly available retrieval data and achieves state-of-the-art embedding performance on the MTEB benchmark. |