3 citations · 7 across the 24 of their papers we have counts for
12 papers · 1 filter
Controllable Narrative Rendering for Enhanced Assisted Writing
Mingzhe Lu, Yanbing Liu, Jiayue Wu +5
Despite the remarkable proficiency of large language models (LLMs) in basic writing assistance, their utility in creative writing is fundamentally hindered by a persistent binary f…
S^2tory: Story Spine Distillation for Movie Script Summarization
Mingzhe Lu, Yanbing Liu, Qihao Wang +5
Movie scripts pose a fundamental challenge for automatic summarization due to their non-linear, cross-cut narrative structure, which makes surface-level saliency methods ineffectiv…
Local-First Intelligence via Proactive SLM Collaborating with Feedback-Providing LLM
Hang Zeng, Xiangyu Liu, Yong Hu +5
Personal intelligence requires strong capabilities under strict privacy and efficiency constraints. Unlike cloud-first intelligence, which relies on powerful but costly and privacy…
From Myopic Selection to Long-Horizon Awareness: Sequential LLM Routing for Multi-Turn Dialogue
Jiarui Zhang, Xiangyu Liu, Yong Hu +5
Multi-turn dialogue is the predominant form of interaction with large language models (LLMs). While LLM routing is effective in single-turn settings, existing methods fail to maxim…
DuCCAE: A Hybrid Engine for Immersive Conversation via Collaboration, Augmentation, and Evolution
Xin Shen, Zhishu Jiang, Jiaye Yang +13
Immersive conversational systems in production face a persistent trade-off between responsiveness and long-horizon task capability. Real-time interaction is achievable for lightwei…
Toward General Semantic Chunking: A Discriminative Framework for Ultra-Long Documents
Kaifeng Wu, Junyan Wu, Qiang Liu +2
Long-document topic segmentation plays an important role in information retrieval and document understanding, yet existing methods still show clear shortcomings in ultra-long text…
LitVISTA: A Benchmark for Narrative Orchestration in Literary Text
Mingzhe Lu, Yiwen Wang, Yanbing Liu +8
Computational narrative analysis aims to capture rhythm, tension, and emotional dynamics in literary texts. Existing large language models can generate long stories but overly focu…
RAGRouter: Learning to Route Queries to Multiple Retrieval-Augmented Language Models
Jiarui Zhang, Xiangyu Liu, Yong Hu +3
Retrieval-Augmented Generation (RAG) significantly improves the performance of Large Language Models (LLMs) on knowledge-intensive tasks. However, varying response quality across L…
Helping Language Models Learn More: Multi-dimensional Task Prompt for Few-shot Tuning
Jinta Weng, Jiarui Zhang, Yue Hu +3
Large language models (LLMs) can be used as accessible and intelligent chatbots by constructing natural language queries and directly inputting the prompt into the large language m…
Utilizing Background Knowledge for Robust Reasoning over Traffic Situations
Jiarui Zhang, Filip Ilievski, Aravinda Kollaa +3
Understanding novel situations in the traffic domain requires an intricate combination of domain-specific and causal commonsense knowledge. Prior work has provided sufficient perce…
An Empirical Investigation of Commonsense Self-Supervision with Knowledge Graphs
Jiarui Zhang, Filip Ilievski, Kaixin Ma +2
Self-supervision based on the information extracted from large knowledge graphs has been shown to improve the generalization of language models, in zero-shot evaluation on various…
Modeling Discourse Structure for Document-level Neural Machine Translation
Junxuan Chen, Xiang Li, Jiarui Zhang +4
Recently, document-level neural machine translation (NMT) has become a hot topic in the community of machine translation. Despite its success, most of existing studies ignored the…