Search Results for author:
Found 29 papers, 13 papers with code
Towards Human Cognition: Visual Context Guides Syntactic Priming in Fusion-Encoded Models
We introduced PRISMATIC, the first multimodal structural priming dataset, and proposed a reference-free evaluation metric that assesses priming effects without predefined target sentences.
Transformer-Based Multimodal Knowledge Graph Completion with Link-Aware Contexts
Multimodal knowledge graph completion (MMKGC) aims to predict missing links in multimodal knowledge graphs (MMKGs) by leveraging information from various modalities alongside structural data.
RAMQA: A Unified Framework for Retrieval-Augmented Multi-Modal Question Answering
Multi-modal retrieval-augmented Question Answering (MRAQA), integrating text and images, has gained significant attention in information retrieval (IR) and natural language processing (NLP).
TTQA-RS- A break-down prompting approach for Multi-hop Table-Text Question Answering with Reasoning and Summarization
Question answering (QA) over tables and text has gained much popularity over the years.
M3: A Multi-Task Mixed-Objective Learning Framework for Open-Domain Multi-Hop Dense Sentence Retrieval
In recent research, contrastive learning has proven to be a highly effective method for representation learning and is widely used for dense retrieval.
No more optimization rules: LLM-enabled policy-based multi-modal query optimizer
As a critical (or could even be the most important) step that significantly impacts the execution performance of the query plan, such analysis and attempts should not be missed.
Xling: A Learned Filter Framework for Accelerating High-Dimensional Approximate Similarity Join
In this paper, we propose Xling, a generic framework to build a learning-based metric space filter with any existing regression model, aiming at accurately predicting whether a query point has enough number of neighbors.
Question Answering for Electronic Health Records: A Scoping Review of datasets and models
Because of the differences in data format and modality, this differs greatly from other medical QA tasks that employ medical websites or scientific papers to retrieve answers, making it critical to research EHR question answering.
Can Knowledge Graphs Simplify Text?
Knowledge Graph (KG)-to-Text Generation has seen recent improvements in generating fluent and informative sentences which describe a given KG.
Simple Rule Injection for ComplEx Embeddings
Recent works in neural knowledge graph inference attempt to combine logic rules with knowledge graph embeddings to benefit from prior knowledge.
MythQA: Query-Based Large-Scale Check-Worthy Claim Detection through Multi-Answer Open-Domain Question Answering
The idea behind this is that contradictory claims are a strong indicator of misinformation that merits scrutiny by the appropriate authorities.
Reasoning with Language Model is Planning with World Model
RAP on LLAMA-33B surpasses CoT on GPT-4 with 33% relative improvement in a plan generation setting.
Learned Accelerator Framework for Angular-Distance-Based High-Dimensional DBSCAN
In this paper, we propose LAF, a generic learned accelerator framework to speed up the original DBSCAN and the sampling-based variants of DBSCAN on high-dimensional data with angular distance metric.
A Survey On Few-shot Knowledge Graph Completion with Structural and Commonsense Knowledge
In this paper, we comprehensively survey previous attempts on such tasks in the form of a series of methods and applications.
Query-Driven Knowledge Base Completion using Multimodal Path Fusion over Multimodal Knowledge Graph
Over the past few years, large knowledge bases have been constructed to store massive amounts of knowledge.
Knowledge Base Completion using Web-Based Question Answering and Multimodal Fusion
Over the past few years, large knowledge bases have been constructed to store massive amounts of knowledge.
DrugEHRQA: A Question Answering Dataset on Structured and Unstructured Electronic Health Records For Medicine Related Queries
Our goal is to provide a benchmark dataset for multi-modal QA systems, and to open up new avenues of research in improving question answering over EHR structured data by using context from unstructured clinical data.
LIDER: An Efficient High-dimensional Learned Index for Large-scale Dense Passage Retrieval
As the basic unit of LIDER to index and search data, a core model includes an adapted recursive model index (RMI) and a dimension reduction component which consists of an extended SortingKeys-LSH (SK-LSH) and a key re-scaling module.
GAP: A Graph-aware Language Model Framework for Knowledge Graph-to-Text Generation
Recent improvements in KG-to-text generation are due to additional auxiliary pre-training tasks designed to give the fine-tune task a boost in performance.
Ranked #1 on
KG-to-Text Generation
on EventNarrative
EventNarrative: A large-scale Event-centric Dataset for Knowledge Graph-to-Text Generation
We also evaluate two types of baseline on EventNarrative: a graph-to-text specific model and two state-of-the-art language models, which previous work has shown to be adaptable to the knowledge graph-to-text domain.
Ranked #3 on
KG-to-Text Generation
on EventNarrative
More Than Reading Comprehension: A Survey on Datasets and Metrics of Textual Question Answering
Textual Question Answering (QA) aims to provide precise answers to user's questions in natural language using unstructured data.
ChronoR: Rotation Based Temporal Knowledge Graph Embedding
In particular, the task of temporal link prediction.
TutorialVQA: Question Answering Dataset for Tutorial Videos
The results indicate that the task is challenging and call for the investigation of new algorithms.
DRUM: End-To-End Differentiable Rule Mining On Knowledge Graphs
Despite the importance of inductive link prediction, most previous works focused on transductive link prediction and cannot manage previously unseen entities.
Ranked #18 on
Link Prediction
on WN18RR
Inductive knowledge graph completion
Inductive Link Prediction
+2
Measuring Impact of Climate Change on Tree Species: analysis of JSDM on FIA data
In this study tree species interaction and the response to climate in different ecological environments is observed by applying a joint species distribution model to different ecological domains in the United States.
Populations and Evolution
Hotel2vec: Learning Attribute-Aware Hotel Embeddings with Self-Supervision
We propose a neural network architecture for learning vector representations of hotels.
Mining Rules Incrementally over Large Knowledge Bases
To the best of our knowledge, our incremental rule mining system is the first that handles updates to web-scale knowledge bases.
