Search Results for author:
Found 19 papers, 8 papers with code
Frustratingly Simple but Surprisingly Strong: Using Language-Independent Features for Zero-shot Cross-lingual Semantic Parsing
The availability of corpora has led to significant advances in training semantic parsers in English.
WIKIBIAS: Detecting Multi-Span Subjective Biases in Language
Biases continue to be prevalent in modern text and media, especially subjective bias – a special type of bias that introduces improper attitudes or presents a statement with the presupposition of truth.
Planning and Generating Natural and Diverse Disfluent Texts as Augmentation for Disfluency Detection
Existing approaches to disfluency detection heavily depend on human-annotated data.
GrowLength: Accelerating LLMs Pretraining by Progressively Growing Training Length
Our method progressively increases the training length throughout the pretraining phase, thereby mitigating computational costs and enhancing efficiency.
Situated Natural Language Explanations
To address this limitation, we propose an alternative perspective, situated NLE, including a situated generation framework and a situated evaluation framework.
CCGen: Explainable Complementary Concept Generation in E-Commerce
We propose and study Complementary Concept Generation (CCGen): given a concept of interest, e. g., "Digital Cameras", generating a list of complementary concepts, e. g., 1) Camera Lenses 2) Batteries 3) Camera Cases 4) Memory Cards 5) Battery Chargers.
Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond
This paper presents a comprehensive and practical guide for practitioners and end-users working with Large Language Models (LLMs) in their downstream natural language processing (NLP) tasks.
Mutually-paced Knowledge Distillation for Cross-lingual Temporal Knowledge Graph Reasoning
This paper investigates cross-lingual temporal knowledge graph reasoning problem, which aims to facilitate reasoning on Temporal Knowledge Graphs (TKGs) in low-resource languages by transfering knowledge from TKGs in high-resource ones.
Choice Fusion as Knowledge for Zero-Shot Dialogue State Tracking
With the demanding need for deploying dialogue systems in new domains with less cost, zero-shot dialogue state tracking (DST), which tracks user's requirements in task-oriented dialogues without training on desired domains, draws attention increasingly.
Multi-VALUE: A Framework for Cross-Dialectal English NLP
First, we use this system to stress tests question answering, machine translation, and semantic parsing.
On the Security Vulnerabilities of Text-to-SQL Models
Although it has been demonstrated that Natural Language Processing (NLP) algorithms are vulnerable to deliberate attacks, the question of whether such weaknesses can lead to software security threats is under-explored.
SeqZero: Few-shot Compositional Semantic Parsing with Sequential Prompts and Zero-shot Models
SeqZero achieves SOTA performance of BART-based models on GeoQuery and EcommerceQuery, which are two few-shot datasets with compositional data split.
SUBS: Subtree Substitution for Compositional Semantic Parsing
Although sequence-to-sequence models often achieve good performance in semantic parsing for i. i. d.
TableFormer: Robust Transformer Modeling for Table-Text Encoding
Existing models for table understanding require linearization of the table structure, where row or column order is encoded as an unwanted bias.
LR-CNN: Local-aware Region CNN for Vehicle Detection in Aerial Imagery
This strengthens the local feature invariance for the resampled features and enables detecting vehicles in an arbitrary orientation.
A survey of cross-lingual features for zero-shot cross-lingual semantic parsing
The availability of corpora to train semantic parsers in English has lead to significant advances in the field.
Chinese Discourse Segmentation Using Bilingual Discourse Commonality
Discourse segmentation aims to segment Elementary Discourse Units (EDUs) and is a fundamental task in discourse analysis.
Toward Fast and Accurate Neural Discourse Segmentation
Discourse segmentation, which segments texts into Elementary Discourse Units, is a fundamental step in discourse analysis.
Tag-Enhanced Tree-Structured Neural Networks for Implicit Discourse Relation Classification
Identifying implicit discourse relations between text spans is a challenging task because it requires understanding the meaning of the text.
General Classification
Implicit Discourse Relation Classification
+2
