Search Results for author:
Found 15 papers, 10 papers with code
Zero-Shot Verification-guided Chain of Thoughts
We evaluate the verifiers' ability to classify the correctness of reasoning chains and explore different ways to use verifier scores in guiding reasoning for various mathematical and commonsense reasoning tasks with different LLMs.
On the Design Space Between Transformers and Recursive Neural Nets
In this paper, we study two classes of models, Recursive Neural Networks (RvNNs) and Transformers, and show that a tight connection between them emerges from the recent development of two recent models - Continuous Recursive Neural Networks (CRvNN) and Neural Data Routers (NDR).
Investigating Recurrent Transformers with Dynamic Halt
In this paper, we comprehensively study the inductive biases of two major approaches to augmenting Transformers with a recurrent mechanism: (1) the approach of incorporating a depth-wise recurrence similar to Universal Transformers; and (2) the approach of incorporating a chunk-wise temporal recurrence like Temporal Latent Bottleneck.
Monotonic Location Attention for Length Generalization
We explore different ways to utilize position-based cross-attention in seq2seq networks to enable length generalization in algorithmic tasks.
Beam Tree Recursive Cells
We propose Beam Tree Recursive Cell (BT-Cell) - a backpropagation-friendly framework to extend Recursive Neural Networks (RvNNs) with beam search for latent structure induction.
Data Augmentation for Low-Resource Keyphrase Generation
Very few works address the problem of keyphrase generation in low-resource settings, but they still rely on a lot of additional unlabeled data for pretraining and on automatic methods for pseudo-annotations.
Neural Keyphrase Generation: Analysis and Evaluation
Keyphrase generation aims at generating topical phrases from a given text either by copying from the original text (present keyphrases) or by producing new keyphrases (absent keyphrases) that capture the semantic meaning of the text.
On the Evaluation of Answer-Agnostic Paragraph-level Multi-Question Generation
Second, we compare different strategies to utilize a pre-trained seq2seq model to generate and select a set of questions related to a given paragraph.
Novelty Controlled Paraphrase Generation with Retrieval Augmented Conditional Prompt Tuning
Paraphrase generation is a fundamental and long-standing task in natural language processing.
Keyphrase Generation Beyond the Boundaries of Title and Abstract
Unlike prior large-scale datasets, FullTextKP includes the full text of the articles along with the title and abstract.
KPDrop: Improving Absent Keyphrase Generation
Keyphrase generation is the task of generating phrases (keyphrases) that summarize the main topics of a given document.
Modeling Hierarchical Structures with Continuous Recursive Neural Networks
We also show that CRvNN performs comparably or better than prior latent structure models on real-world tasks such as sentiment analysis and natural language inference.
Cross-Lingual Disaster-related Multi-label Tweet Classification with Manifold Mixup
Distinguishing informative and actionable messages from a social media platform like Twitter is critical for facilitating disaster management.
On Identifying Hashtags in Disaster Twitter Data
Moreover, only a small number of tweets that contain actionable hashtags are useful for disaster response.
Keyphrase Extraction from Disaster-related Tweets
Previously, joint training of two different layers of a stacked Recurrent Neural Network for keyword discovery and keyphrase extraction had been shown to be effective in extracting keyphrases from general Twitter data.
