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20242026
most citedQAEA-DR: A Unified Text Augmentation Framework for Dense Retrieval

5 citations · 11 across the 9 of their papers we have counts for

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cs.CL2026

SemantiCache: Efficient KV Cache Compression via Semantic Chunking and Clustered Merging

Shunlong Wu, Hai Lin, Shaoshen Chen +5

Existing KV cache compression methods generally operate on discrete tokens or non-semantic chunks. However, such approaches often lead to semantic fragmentation, where linguistical…

cs.CL2026★ 2 cited

ERNIE 5.0 Technical Report

Haifeng Wang, Hua Wu, Tian Wu +432

In this report, we introduce ERNIE 5.0, a natively autoregressive foundation model desinged for unified multimodal understanding and generation across text, image, video, and audio…

cs.CL2025

Auxiliary-Hyperparameter-Free Sampling: Entropy Equilibrium for Text Generation

Xiaodong Cai, Hai Lin, Shaoxiong Zhan +5

Token sampling strategies critically influence text generation quality in large language models (LLMs). However, existing methods introduce additional hyperparameters, requiring ex…

cs.CL2024★ 5 cited

QAEA-DR: A Unified Text Augmentation Framework for Dense Retrieval

Hongming Tan, Shaoxiong Zhan, Hai Lin +2

In dense retrieval, embedding long texts into dense vectors can result in information loss, leading to inaccurate query-text matching. Additionally, low-quality texts with excessiv…

cs.CL2024

OpenFMNav: Towards Open-Set Zero-Shot Object Navigation via Vision-Language Foundation Models

Yuxuan Kuang, Hai Lin, Meng Jiang

Object navigation (ObjectNav) requires an agent to navigate through unseen environments to find queried objects. Many previous methods attempted to solve this task by relying on su…