Search Results for author:
Found 7 papers, 3 papers with code
MARVEL: Multidimensional Abstraction and Reasoning through Visual Evaluation and Learning
Further analysis of perception questions reveals that MLLMs struggle to comprehend the visual features (near-random performance) and even count the panels in the puzzle ( <45%), hindering their ability for abstract reasoning.
The Curious Case of Nonverbal Abstract Reasoning with Multi-Modal Large Language Models
While large language models (LLMs) are still being adopted to new domains and utilized in novel applications, we are experiencing an influx of the new generation of foundation models, namely multi-modal large language models (MLLMs).
Temporal Knowledge Graph Forecasting Without Knowledge Using In-Context Learning
This shows that prior semantic knowledge is unnecessary; instead, LLMs can leverage the existing patterns in the context to achieve such performance.
PubGraph: A Large-Scale Scientific Knowledge Graph
In this paper, we present PubGraph, a new resource for studying scientific progress that takes the form of a large-scale knowledge graph (KG) with more than 385M entities, 13B main edges, and 1. 5B qualifier edges.
Structure Aware Negative Sampling in Knowledge Graphs
Learning low-dimensional representations for entities and relations in knowledge graphs using contrastive estimation represents a scalable and effective method for inferring connectivity patterns.
Software Engineering Event Modeling using Relative Time in Temporal Knowledge Graphs
We present a multi-relational temporal Knowledge Graph based on the daily interactions between artifacts in GitHub, one of the largest social coding platforms.
On Usage of Autoencoders and Siamese Networks for Online Handwritten Signature Verification
In this paper, we propose a novel writer-independent global feature extraction framework for the task of automatic signature verification which aims to make robust systems for automatically distinguishing negative and positive samples.
