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20242026
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cs.CL2026

Large Language Model-Powered Query-Driven Event Timeline Summarization in Industrial Search

Mingyue Wang, Xingyu Xie, Hang Yang +5

Understanding how events evolve over time is essential for search engines handling queries about trending news. We present QDET (Query-Driven Event Timeline Summarization), a produ…

cs.CL2026

Towards AI Search Paradigm

Yuchen Li, Hengyi Cai, Rui Kong +20

In this paper, we introduce the AI Search Paradigm, a comprehensive blueprint for next-generation search systems capable of emulating human information processing and decision-maki…

cs.CL2025

Behavior-Equivalent Token: Single-Token Replacement for Long Prompts in LLMs

Jiancheng Dong, Pengyue Jia, Jingyu Peng +7

Carefully engineered system prompts play a critical role in guiding the behavior of LLM agents, but their considerable length introduces significant drawbacks, including increased…

cs.CL2025

CoRanking: Collaborative Ranking with Small and Large Ranking Agents

Wenhan Liu, Xinyu Ma, Yutao Zhu +4

Large Language Models (LLMs) have demonstrated superior listwise ranking performance. However, their superior performance often relies on large-scale parameters (\eg, GPT-4) and a…

cs.CL2025

TP-RAG: Benchmarking Retrieval-Augmented Large Language Model Agents for Spatiotemporal-Aware Travel Planning

Hang Ni, Fan Liu, Xinyu Ma +5

Large language models (LLMs) have shown promise in automating travel planning, yet they often fall short in addressing nuanced spatiotemporal rationality. While existing benchmarks…

cs.CL2024

Cross-model Control: Improving Multiple Large Language Models in One-time Training

Jiayi Wu, Hao Sun, Hengyi Cai +5

The number of large language models (LLMs) with varying parameter scales and vocabularies is increasing. While they deliver powerful performance, they also face a set of common opt…