5 citations · 9 across the 15 of their papers we have counts for
9 papers · 1 filter
Factorized Hypothesis Search for Evidence-to-Taxonomy Retrieval
Linhai Ma, Ethan F. Wei, Xueqing Peng +3
Large-taxonomy retrieval often assumes that the input already expresses the target concept. In many settings, however, the input is indirect evidence, such as a table cell whose me…
From Sufficiency to Reflection: Reinforcement-Guided Thinking Quality in Retrieval-Augmented Reasoning for LLMs
Jie He, Victor Gutiérrez-Basulto, Jeff Z. Pan
Reinforcement learning-based retrieval-augmented generation (RAG) methods enhance the reasoning abilities of large language models (LLMs). However, most rely only on final-answer r…
N2C2: Nearest Neighbor Enhanced Confidence Calibration for Cross-Lingual In-Context Learning
Jie He, Simon Yu, Deyi Xiong +2
Recent advancements of in-context learning (ICL) show language models can significantly improve their performance when demonstrations are provided. However, little attention has be…
An Empirical Study on Parameter-Efficient Fine-Tuning for MultiModal Large Language Models
Xiongtao Zhou, Jie He, Yuhua Ke +3
Multimodal large language models (MLLMs) fine-tuned with multimodal instruction datasets have demonstrated remarkable capabilities in multimodal tasks. However, fine-tuning all par…
BLEnD: A Benchmark for LLMs on Everyday Knowledge in Diverse Cultures and Languages
Junho Myung, Nayeon Lee, Yi Zhou +19
Large language models (LLMs) often lack culture-specific knowledge of daily life, especially across diverse regions and non-English languages. Existing benchmarks for evaluating LL…
UniArk: Improving Generalisation and Consistency for Factual Knowledge Extraction through Debiasing
Yijun Yang, Jie He, Pinzhen Chen +2
Several recent papers have investigated the potential of language models as knowledge bases as well as the existence of severe biases when extracting factual knowledge. In this wor…
Multi-view Contrastive Learning for Entity Typing over Knowledge Graphs
Zhiwei Hu, Víctor Gutiérrez-Basulto, Zhiliang Xiang +2
Knowledge graph entity typing (KGET) aims at inferring plausible types of entities in knowledge graphs. Existing approaches to KGET focus on how to better encode the knowledge prov…
Instances and Labels: Hierarchy-aware Joint Supervised Contrastive Learning for Hierarchical Multi-Label Text Classification
Simon Yu, Jie He, Víctor Gutiérrez-Basulto +1
Hierarchical multi-label text classification (HMTC) aims at utilizing a label hierarchy in multi-label classification. Recent approaches to HMTC deal with the problem of imposing a…
BUCA: A Binary Classification Approach to Unsupervised Commonsense Question Answering
Jie He, Simon Chi Lok U, Víctor Gutiérrez-Basulto +1
Unsupervised commonsense reasoning (UCR) is becoming increasingly popular as the construction of commonsense reasoning datasets is expensive, and they are inevitably limited in the…