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Found 14 papers, 5 papers with code
Modality-specific Distillation
In this paper, we propose modality-specific distillation (MSD) to effectively transfer knowledge from a teacher on multimodal datasets.
Recurrent Event Network: Autoregressive Structure Inferenceover Temporal Knowledge Graphs
The task becomes more challenging on temporal knowledge graphs, where each fact is associated with a timestamp.
WinoViz: Probing Visual Properties of Objects Under Different States
We present WinoViz, a text-only evaluation dataset, consisting of 1, 380 examples that probe the reasoning abilities of language models regarding variant visual properties of objects under different contexts or states.
GRILL: Grounded Vision-language Pre-training via Aligning Text and Image Regions
Generalization to unseen tasks is an important ability for few-shot learners to achieve better zero-/few-shot performance on diverse tasks.
Analyzing Norm Violations in Live-Stream Chat
Previous approaches to detecting toxic language and norm violations have been primarily concerned with conversations from online forums and social media, such as Reddit and Twitter.
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.
Leveraging Visual Knowledge in Language Tasks: An Empirical Study on Intermediate Pre-training for Cross-modal Knowledge Transfer
Pre-trained language models are still far from human performance in tasks that need understanding of properties (e. g. appearance, measurable quantity) and affordances of everyday objects in the real world since the text lacks such information due to reporting bias.
A Good Prompt Is Worth Millions of Parameters: Low-resource Prompt-based Learning for Vision-Language Models
Large pre-trained vision-language (VL) models can learn a new task with a handful of examples and generalize to a new task without fine-tuning.
Ranked #4 on
Image Captioning
on Flickr30k Captions test
(SPICE metric)
MSD: Saliency-aware Knowledge Distillation for Multimodal Understanding
The idea aims at mimicking a teacher's modality-specific predictions by introducing auxiliary loss terms for each modality.
ForecastQA: A Question Answering Challenge for Event Forecasting with Temporal Text Data
In this work, we aim to formulate a task, construct a dataset, and provide benchmarks for developing methods for event forecasting with large volumes of unstructured text data.
Temporal Attribute Prediction via Joint Modeling of Multi-Relational Structure Evolution
We show that if the information contained in the graph and the time series data are closely related, then this inter-dependence can be used to predict the time series with improved accuracy.
Recurrent Event Network : Global Structure Inference Over Temporal Knowledge Graph
We present Recurrent Event Network (RE-Net), a novel autoregressive architecture for modeling temporal sequences of multi-relational graphs (e. g., temporal knowledge graph), which can perform sequential, global structure inference over future time stamps to predict new events.
Collaborative Policy Learning for Open Knowledge Graph Reasoning
We propose a novel reinforcement learning framework to train two collaborative agents jointly, i. e., a multi-hop graph reasoner and a fact extractor.
Recurrent Event Network: Autoregressive Structure Inference over Temporal Knowledge Graphs
The task becomes more challenging on temporal knowledge graphs, where each fact is associated with a timestamp.
