30 citations · 101 across the 45 of their papers we have counts for
47 papers
RALI@iKAT 2026: Retrieval-aware User Profile Denoising via Personalized Conversational Dense Retrieval
Yuchen Hui, Fengran Mo, Jia Ao Sun +3
Modern conversational information access systems continuously extract user information from conversations to build user profiles for personalized retrieval. As user profiles accumu…
Search-on-Graph-R1: Training Large Language Models to Search Knowledge Graphs with Reinforcement Learning
Jia Ao Sun, Hao Yu, Fengran Mo +4
Knowledge graph question answering (KGQA) requires navigating from topic entities to an answer several relations away. Recent methods prompt a frontier LLM to explore the graph thr…
Learning to Route Queries to Heads for Attention-based Re-ranking with Large Language Models
Yuxing Tian, Fengran Mo, Zhiqi Huang +2
Large Language Models (LLMs) have recently been explored as fine-grained zero-shot re-rankers by leveraging attention signals to estimate document relevance. However, existing meth…
ReAttn: Improving Attention-based Re-ranking via Attention Re-weighting
Yuxing Tian, Fengran Mo, Weixu Zhang +2
The strong capabilities of recent Large Language Models (LLMs) have made them highly effective for zero-shot re-ranking task. Attention-based re-ranking methods, which derive relev…
Learning Discriminative and Generalizable Anomaly Detector for Dynamic Graph with Limited Supervision
Yuxing Tian, Yiyan Qi, Fengran Mo +3
Dynamic graph anomaly detection is critical for many real-world applications but remains challenging due to the scarcity of labeled anomalies. Existing methods are either unsupervi…
Conv-FinRe: A Conversational and Longitudinal Benchmark for Utility-Grounded Financial Recommendation
Yan Wang, Yi Han, Lingfei Qian +11
Most recommendation benchmarks evaluate how well a model imitates user behavior. In financial advisory, however, observed actions can be noisy or short-sighted under market volatil…
OpenDecoder: Open Large Language Model Decoding to Incorporate Document Quality in RAG
Fengran Mo, Zhan Su, Yuchen Hui +6
The development of large language models (LLMs) has achieved superior performance in a range of downstream tasks, including LLM-based retrieval-augmented generation (RAG). The qual…
Language-Coupled Reinforcement Learning for Multilingual Retrieval-Augmented Generation
Rui Qi, Fengran Mo, Yufeng Chen +6
Multilingual retrieval-augmented generation (MRAG) requires models to effectively acquire and integrate beneficial external knowledge from multilingual collections. However, most e…
When Helpers Become Hazards: A Benchmark for Analyzing Multimodal LLM-Powered Safety in Daily Life
Xinyue Lou, Jinan Xu, Jingyi Yin +8
As Multimodal Large Language Models (MLLMs) become an indispensable assistant in human life, the unsafe content generated by MLLMs poses a danger to human behavior, perpetually ove…
Measuring the Impact of Lexical Training Data Coverage on Hallucination Detection in Large Language Models
Shuo Zhang, Fabrizio Gotti, Fengran Mo +1
Hallucination in large language models (LLMs) is a fundamental challenge, particularly in open-domain question answering. Prior work attempts to detect hallucination with model-int…
CSMD: Curated Multimodal Dataset for Chinese Stock Analysis
Yu Liu, Zhuoying Li, Ruifeng Yang +2
The stock market is a complex and dynamic system, where it is non-trivial for researchers and practitioners to uncover underlying patterns and forecast stock movements. The existin…
Parametric Retrieval-Augmented Generation using Latent Routing of LoRA Adapters
Zhan Su, Fengran Mo, Jinghan Zhang +3
Parametric Retrieval-Augmented Generation (PRAG) is a RAG approach that integrates external knowledge directly into model parameters using a LoRA adapter, aiming at reducing the in…
SoT: Structured-of-Thought Prompting Guides Multilingual Reasoning in Large Language Models
Rui Qi, Zhibo Man, Yufeng Chen +3
Recent developments have enabled Large Language Models (LLMs) to engage in complex reasoning tasks through deep thinking. However, the capacity of reasoning has not been successful…
FinAuditing: A Financial Taxonomy-Structured Multi-Document Benchmark for Evaluating LLMs
Yan Wang, Keyi Wang, Shanshan Yang +12
Going beyond simple text processing, financial auditing requires detecting semantic, structural, and numerical inconsistencies across large-scale disclosures. As financial reports…
Search-on-Graph: Iterative Informed Navigation for Large Language Model Reasoning on Knowledge Graphs
Jia Ao Sun, Hao Yu, Fabrizio Gotti +6
Large language models (LLMs) augmented with knowledge graphs (KGs) offer a promising approach for knowledge-intensive reasoning. Central to this approach is the selection of approp…
Boosting Data Utilization for Multilingual Dense Retrieval
Chao Huang, Fengran Mo, Yufeng Chen +5
Multilingual dense retrieval aims to retrieve relevant documents across different languages based on a unified retriever model. The challenge lies in aligning representations of di…
Adaptive Personalized Conversational Information Retrieval
Fengran Mo, Yuchen Hui, Yuxing Tian +5
Personalized conversational information retrieval (CIR) systems aim to satisfy users' complex information needs through multi-turn interactions by considering user profiles. Howeve…
Tensorized Clustered LoRA Merging for Multi-Task Interference
Zhan Su, Fengran Mo, Guojun Liang +4
Despite the success of the monolithic dense paradigm of large language models (LLMs), the LoRA adapters offer an efficient solution by fine-tuning small task-specific modules and m…
ConvMix: A Mixed-Criteria Data Augmentation Framework for Conversational Dense Retrieval
Fengran Mo, Jinghan Zhang, Yuchen Hui +4
Conversational search aims to satisfy users' complex information needs via multiple-turn interactions. The key challenge lies in revealing real users' search intent from the contex…
An Entity Linking Agent for Question Answering
Yajie Luo, Yihong Wu, Muzhi Li +5
Some Question Answering (QA) systems rely on knowledge bases (KBs) to provide accurate answers. Entity Linking (EL) plays a critical role in linking natural language mentions to KB…
Smooth Reading: Bridging the Gap of Recurrent LLM to Self-Attention LLM on Long-Context Tasks
Kai Liu, Zhan Su, Peijie Dong +4
Recently, recurrent large language models (Recurrent LLMs) with linear computational complexity have re-emerged as efficient alternatives to self-attention-based LLMs (Self-Attenti…
Conversational Search: From Fundamentals to Frontiers in the LLM Era
Fengran Mo, Chuan Meng, Mohammad Aliannejadi +1
Conversational search enables multi-turn interactions between users and systems to fulfill users' complex information needs. During this interaction, the system should understand t…
FinTagging: Benchmarking LLMs for Extracting and Structuring Financial Information
Yan Wang, Lingfei Qian, Xueqing Peng +18
Accurate interpretation of numerical data in financial reports is critical for markets and regulators. Although XBRL (eXtensible Business Reporting Language) provides a standard fo…
Multilingual Collaborative Defense for Large Language Models
Hongliang Li, Jinan Xu, Gengping Cui +3
The robustness and security of large language models (LLMs) has become a prominent research area. One notable vulnerability is the ability to bypass LLM safeguards by translating h…