6 citations · 25 across the 13 of their papers we have counts for
13 papers
MM-ARC: Multimodal Adaptive Routing of Capital with Robustness-Audited Strategy Pools
Yang Chen, Yuchen Cao, Jacky Keung +7
Financial trading systems must convert multimodal market history into executable positions while limiting overfitting from repeated strategy search. We introduce MM-ARC (MultiModal…
Evaluating Test-Time Scaling LLMs for Legal Reasoning: OpenAI o1, DeepSeek-R1, and Beyond
Yinghao Hu, Yaoyao Yu, Leilei Gan +3
Recent advances in test-time scaling of large language models (LLMs), exemplified by DeepSeek-R1 and OpenAI's o1, show that extending the chain of thought during inference can sign…
Fine-tuning Large Language Models for Improving Factuality in Legal Question Answering
Yinghao Hu, Leilei Gan, Wenyi Xiao +2
Hallucination, or the generation of incorrect or fabricated information, remains a critical challenge in large language models (LLMs), particularly in high-stake domains such as le…
Retrieval-Augmented Mixture of LoRA Experts for Uploadable Machine Learning
Ziyu Zhao, Leilei Gan, Guoyin Wang +5
Low-Rank Adaptation (LoRA) offers an efficient way to fine-tune large language models (LLMs). Its modular and plug-and-play nature allows the integration of various domain-specific…
Detecting and Mitigating Hallucination in Large Vision Language Models via Fine-Grained AI Feedback
Wenyi Xiao, Ziwei Huang, Leilei Gan +6
The rapidly developing Large Vision Language Models (LVLMs) have shown notable capabilities on a range of multi-modal tasks, but still face the hallucination phenomena where the ge…
LoraRetriever: Input-Aware LoRA Retrieval and Composition for Mixed Tasks in the Wild
Ziyu Zhao, Leilei Gan, Guoyin Wang +4
Low-Rank Adaptation (LoRA) provides an effective yet efficient solution for fine-tuning large language models (LLM). The modular and plug-and-play nature of LoRA enables the integr…
Exploiting Contrastive Learning and Numerical Evidence for Confusing Legal Judgment Prediction
Leilei Gan, Baokui Li, Kun Kuang +5
Given the fact description text of a legal case, legal judgment prediction (LJP) aims to predict the case's charge, law article and penalty term. A core problem of LJP is how to di…
Investigating the Robustness of Natural Language Generation from Logical Forms via Counterfactual Samples
Chengyuan Liu, Leilei Gan, Kun Kuang +1
The aim of Logic2Text is to generate controllable and faithful texts conditioned on tables and logical forms, which not only requires a deep understanding of the tables and logical…
Dialogue Inspectional Summarization with Factual Inconsistency Awareness
Leilei Gan, Yating Zhang, Kun Kuang +5
Dialogue summarization has been extensively studied and applied, where the prior works mainly focused on exploring superior model structures to align the input dialogue and the out…
Triggerless Backdoor Attack for NLP Tasks with Clean Labels
Leilei Gan, Jiwei Li, Tianwei Zhang +6
Backdoor attacks pose a new threat to NLP models. A standard strategy to construct poisoned data in backdoor attacks is to insert triggers (e.g., rare words) into selected sentence…
Dependency Parsing as MRC-based Span-Span Prediction
Leilei Gan, Yuxian Meng, Kun Kuang +4
Higher-order methods for dependency parsing can partially but not fully address the issue that edges in dependency trees should be constructed at the text span/subtree level rather…
SemGloVe: Semantic Co-occurrences for GloVe from BERT
Leilei Gan, Zhiyang Teng, Yue Zhang +3
GloVe learns word embeddings by leveraging statistical information from word co-occurrence matrices. However, word pairs in the matrices are extracted from a predefined local conte…
Investigating Self-Attention Network for Chinese Word Segmentation
Leilei Gan, Yue Zhang
Neural network has become the dominant method for Chinese word segmentation. Most existing models cast the task as sequence labeling, using BiLSTM-CRF for representing the input an…