activity
20202026
most citedThe Factual Inconsistency Problem in Abstractive Text Summarization: A Survey

67 citations · 108 across the 27 of their papers we have counts for

collaborators

29 papers

cs.CL2026

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…

cs.AI2026

The Granularity Axis: A Micro-to-Macro Latent Direction for Social Roles in Language Models

Chonghan Qin, Xiachong Feng, Ziyun Song +3

Large language models (LLMs) are routinely prompted to take on social roles ranging from individuals to institutions, yet it remains unclear whether their internal representations…

cs.AI2026

SAVOIR: Learning Social Savoir-Faire via Shapley-based Reward Attribution

Xiachong Feng, Yi Jiang, Xiaocheng Feng +9

Social intelligence, the ability to navigate complex interpersonal interactions, presents a fundamental challenge for language agents. Training such agents via reinforcement learni…

cs.AI2026

Stratagem: Learning Transferable Reasoning via Trajectory-Modulated Game Self-Play

Xiachong Feng, Deyi Yin, Xiaocheng Feng +9

Games offer a compelling paradigm for developing general reasoning capabilities in language models, as they naturally demand strategic planning, probabilistic inference, and adapti…

cs.CL2026

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,…

cs.AI2026

ImplicitMemBench: Measuring Unconscious Behavioral Adaptation in Large Language Models

Chonghan Qin, Xiachong Feng, Weitao Ma +2

Existing memory benchmarks for LLM agents evaluate explicit recall of facts, yet overlook implicit memory where experience becomes automated behavior without conscious retrieval. T…

cs.AI2026

PERSONA: Dynamic and Compositional Inference-Time Personality Control via Activation Vector Algebra

Xiachong Feng, Liang Zhao, Weihong Zhong +5

Current methods for personality control in Large Language Models rely on static prompting or expensive fine-tuning, failing to capture the dynamic and compositional nature of human…

cs.CL2026

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…

cs.CV2025

Causal Tracing of Object Representations in Large Vision Language Models: Mechanistic Interpretability and Hallucination Mitigation

Qiming Li, Zekai Ye, Xiaocheng Feng +3

Despite the remarkable advancements of Large Vision-Language Models (LVLMs), the mechanistic interpretability remains underexplored. Existing analyses are insufficiently comprehens…

cs.CL2025

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…

cs.CV2025

Unlocking Multilingual Reasoning Capability of LLMs and LVLMs through Representation Engineering

Qiming Li, Xiaocheng Feng, Yixuan Ma +4

Large Language Models (LLMs) and Large Vision-Language Models (LVLMs) demonstrate strong reasoning capabilities, yet their performance in English significantly outperforms that in…

cs.CR2025

Adaptive Backtracking for Privacy Protection in Large Language Models

Zhihao Yao, Yuxuan Gu, Xiachong Feng +3

The preservation of privacy has emerged as a critical topic in the era of artificial intelligence. However, current work focuses on user-oriented privacy, overlooking severe enterp…

cs.CL2025

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…

cs.CL2025

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…

cs.AI2025

From Hypothesis to Publication: A Comprehensive Survey of AI-Driven Research Support Systems

Zekun Zhou, Xiaocheng Feng, Lei Huang +11

Research is a fundamental process driving the advancement of human civilization, yet it demands substantial time and effort from researchers. In recent years, the rapid development…

cs.CL2025

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…

cs.CV2024

Cross-Lingual Text-Rich Visual Comprehension: An Information Theory Perspective

Xinmiao Yu, Xiaocheng Feng, Yun Li +10

Recent Large Vision-Language Models (LVLMs) have shown promising reasoning capabilities on text-rich images from charts, tables, and documents. However, the abundant text within su…

cs.CL2024

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.…

cs.CL2024

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…

cs.CL2024

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…

cs.CL2023★ 3 cited

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…

cs.CL2023

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,…

cs.CL2023

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…

cs.CL2023

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…