Search Results for author:
Found 17 papers, 9 papers with code
A Distributional Approach to Controlled Text Generation
From that optimal representation we then train a target controlled Autoregressive LM through an adaptive distributional variant of Policy Gradient.
GRACE: Discriminator-Guided Chain-of-Thought Reasoning
To address this issue, we propose Guiding chain-of-thought ReAsoning with a CorrectnEss Discriminator (GRACE), a stepwise decoding approach that steers the decoding process towards producing correct reasoning steps.
Few-shot Reranking for Multi-hop QA via Language Model Prompting
To alleviate the need for a large number of labeled question-document pairs for retriever training, we propose PromptRank, which relies on large language models prompting for multi-hop path reranking.
Merging Generated and Retrieved Knowledge for Open-Domain QA
Open-domain question answering (QA) systems are often built with retrieval modules.
BOLT: Fast Energy-based Controlled Text Generation with Tunable Biases
Energy-based models (EBMs) have gained popularity for controlled text generation due to their high applicability to a wide range of constraints.
LitCab: Lightweight Language Model Calibration over Short- and Long-form Responses
For evaluation, we construct CaT, a benchmark consisting of eight text generation tasks, covering responses ranging from short phrases to paragraphs.
Self-Training Pre-Trained Language Models for Zero- and Few-Shot Multi-Dialectal Arabic Sequence Labeling
We propose to self-train pre-trained language models in zero- and few-shot scenarios to improve performance on data-scarce varieties using only resources from data-rich ones.
Exploring Demonstration Ensembling for In-context Learning
The standard approach for ICL is to prompt the LM with concatenated demonstrations followed by the test input.
Source-Aware Training Enables Knowledge Attribution in Language Models
We investigate the problem of intrinsic source citation, where LLMs are required to cite the pretraining source supporting a generated response.
Semantic Source Code Search: A Study of the Past and a Glimpse at the Future
With the recent explosion in the size and complexity of source codebases and software projects, the need for efficient source code search engines has increased dramatically.
Book Success Prediction with Pretrained Sentence Embeddings and Readability Scores
Predicting the potential success of a book in advance is vital in many applications.
Extracting Synonyms from Bilingual Dictionaries
We present our progress in developing a novel algorithm to extract synonyms from bilingual dictionaries.
Zero-Resource Multi-Dialectal Arabic Natural Language Understanding
In this paper, we investigate the zero-shot performance on Dialectal Arabic (DA) when fine-tuning a PLM on modern standard Arabic (MSA) data only -- identifying a significant performance drop when evaluating such models on DA.
A Bag of Tricks for Dialogue Summarization
Dialogue summarization comes with its own peculiar challenges as opposed to news or scientific articles summarization.
Contrastive Training Improves Zero-Shot Classification of Semi-structured Documents
The standard classification setting where categories are fixed during both training and testing falls short in dynamic environments where new document categories could potentially emerge.
Novel Chapter Abstractive Summarization using Spinal Tree Aware Sub-Sentential Content Selection
Summarizing novel chapters is a difficult task due to the input length and the fact that sentences that appear in the desired summaries draw content from multiple places throughout the chapter.
Has It All Been Solved? Open NLP Research Questions Not Solved by Large Language Models
Not surprisingly, this has, in turn, made many NLP researchers -- especially those at the beginning of their careers -- worry about what NLP research area they should focus on.
