In-context learning (ICL) operates by showing language models (LMs) exam...
In the context of multi-step reasoning, language models (LMs) probabilit...
Planning is an important capability of artificial agents that perform
lo...
This work explores the problem of generating task graphs of real-world
a...
Real-world tasks consist of multiple inter-dependent subtasks (e.g., a d...
Recently, Language Models (LMs) instruction-tuned on multiple tasks, als...
Pretrained Language Models (LMs) memorize a vast amount of knowledge dur...
Pre-trained large language models have shown successful progress in many...
We study unsupervised multi-hop reranking for multi-hop QA (MQA) with
op...
Few-shot algorithms aim at learning new tasks provided only a handful of...
We present the zero-shot entity linking task, where mentions must be lin...
In this work, we address the problem of modifying textual attributes of
...
In this work we propose a simple and efficient framework for learning
se...
Modeling the structure of coherent texts is a key NLP problem. The task ...
Modeling the structure of coherent texts is a task of great importance i...
Automatic synthesis of realistic images from text would be interesting a...