67 citations · 108 across the 27 of their papers we have counts for
18 papers · 1 filter
CultureForest: Understanding and Evaluating Cultural Norm Grounded Reasoning in LLMs
Yangfan Ye, Xiaocheng Feng, Jialong Tang +5
Existing research largely reduces cultural intelligence in LLMs to a knowledge-level problem, overlooking whether models can effectively utilize their acquired knowledge in realist…
x1: Learning to Think Adaptively Across Languages and Cultures
Yangfan Ye, Xiaocheng Feng, Xiachong Feng +8
Languages encode distinct abstractions and inductive priors, yet most large language models (LLMs) overlook this diversity by reasoning in a single dominant language. In this work,…
Fine-Mem: Fine-Grained Feedback Alignment for Long-Horizon Memory Management
Weitao Ma, Xiaocheng Feng, Lei Huang +7
Effective memory management is essential for large language model agents to navigate long-horizon tasks. Recent research has explored using Reinforcement Learning to develop specia…
LangGPS: Language Separability Guided Data Pre-Selection for Joint Multilingual Instruction Tuning
Yangfan Ye, Xiaocheng Feng, Xiachong Feng +7
Joint multilingual instruction tuning is a widely adopted approach to improve the multilingual instruction-following ability and downstream performance of large language models (LL…
CC-Tuning: A Cross-Lingual Connection Mechanism for Improving Joint Multilingual Supervised Fine-Tuning
Yangfan Ye, Xiaocheng Feng, Zekun Yuan +11
Current large language models (LLMs) often exhibit imbalanced multilingual capabilities due to their English-centric training corpora. To address this, existing fine-tuning approac…
One for All: Update Parameterized Knowledge Across Multiple Models
Weitao Ma, Xiyuan Du, Xiaocheng Feng +8
Large language models (LLMs) encode vast world knowledge but struggle to stay up-to-date, often leading to errors and hallucinations. Knowledge editing offers an efficient alternat…
Improving Contextual Faithfulness of Large Language Models via Retrieval Heads-Induced Optimization
Lei Huang, Xiaocheng Feng, Weitao Ma +9
Ensuring contextual faithfulness in retrieval-augmented large language models (LLMs) is crucial for building trustworthy information-seeking systems, particularly in long-form ques…
Exploring Cross-lingual Latent Transplantation: Mutual Opportunities and Open Challenges
Yangfan Ye, Xiaocheng Feng, Xiachong Feng +11
Current large language models (LLMs) often exhibit imbalances in multilingual capabilities and cultural adaptability, largely attributed to their English-centric pre-training data.…
GlobeSumm: A Challenging Benchmark Towards Unifying Multi-lingual, Cross-lingual and Multi-document News Summarization
Yangfan Ye, Xiachong Feng, Xiaocheng Feng +6
News summarization in today's global scene can be daunting with its flood of multilingual content and varied viewpoints from different sources. However, current studies often negle…
Learning Fine-Grained Grounded Citations for Attributed Large Language Models
Lei Huang, Xiaocheng Feng, Weitao Ma +8
Despite the impressive performance on information-seeking tasks, large language models (LLMs) still struggle with hallucinations. Attributed LLMs, which augment generated text with…
Length Extrapolation of Transformers: A Survey from the Perspective of Positional Encoding
Liang Zhao, Xiachong Feng, Xiaocheng Feng +6
Built upon the Transformer, large language models (LLMs) have captured worldwide attention due to their remarkable abilities. Nevertheless, all Transformer-based models including L…
Adapter-based Selective Knowledge Distillation for Federated Multi-domain Meeting Summarization
Xiachong Feng, Xiaocheng Feng, Xiyuan Du +2
Meeting summarization has emerged as a promising technique for providing users with condensed summaries. However, existing work has focused on training models on centralized data,…
The Role of Summarization in Generative Agents: A Preliminary Perspective
Xiachong Feng, Xiaocheng Feng, Bing Qin
Generative agents that simulate human society show tremendous potential for further research and practical applications. Specifically, the generative agent architecture comprising…
Hierarchical Catalogue Generation for Literature Review: A Benchmark
Kun Zhu, Xiaocheng Feng, Xiachong Feng +2
Scientific literature review generation aims to extract and organize important information from an abundant collection of reference papers and produces corresponding reviews while…
Language Model as an Annotator: Exploring DialoGPT for Dialogue Summarization
Xiachong Feng, Xiaocheng Feng, Libo Qin +2
Current dialogue summarization systems usually encode the text with a number of general semantic features (e.g., keywords and topics) to gain more powerful dialogue modeling capabi…
The Factual Inconsistency Problem in Abstractive Text Summarization: A Survey
Yichong Huang, Xiachong Feng, Xiaocheng Feng +1
Recently, various neural encoder-decoder models pioneered by Seq2Seq framework have been proposed to achieve the goal of generating more abstractive summaries by learning to map in…
Dialogue Discourse-Aware Graph Model and Data Augmentation for Meeting Summarization
Xiachong Feng, Xiaocheng Feng, Bing Qin +1
Meeting summarization is a challenging task due to its dynamic interaction nature among multiple speakers and lack of sufficient training data. Existing methods view the meeting as…
Incorporating Commonsense Knowledge into Abstractive Dialogue Summarization via Heterogeneous Graph Networks
Xiachong Feng, Xiaocheng Feng, Bing Qin +1
Abstractive dialogue summarization is the task of capturing the highlights of a dialogue and rewriting them into a concise version. In this paper, we present a novel multi-speaker…