Search Results for author:
Found 18 papers, 7 papers with code
BORT: Back and Denoising Reconstruction for End-to-End Task-Oriented Dialog
To enhance the denoising capability of the model to reduce the impact of error propagation, denoising reconstruction is used to reconstruct the corrupted dialog state and response.
LUNA: Learning Slot-Turn Alignment for Dialogue State Tracking
Dialogue state tracking (DST) aims to predict the current dialogue state given the dialogue history.
OPERA:Operation-Pivoted Discrete Reasoning over Text
To inherit the advantages of these two types of methods, we propose OPERA, an operation-pivoted discrete reasoning framework, where lightweight symbolic operations (compared with logical forms) as neural modules are utilized to facilitate the reasoning ability and interpretability.
A Roadmap for Big Model
With the rapid development of deep learning, training Big Models (BMs) for multiple downstream tasks becomes a popular paradigm.
Fine- and Coarse-Granularity Hybrid Self-Attention for Efficient BERT
To confront this, we propose FCA, a fine- and coarse-granularity hybrid self-attention that reduces the computation cost through progressively shortening the computational sequence length in self-attention.
CUGE: A Chinese Language Understanding and Generation Evaluation Benchmark
We argue that for general-purpose language intelligence evaluation, the benchmark itself needs to be comprehensive and systematic.
RoR: Read-over-Read for Long Document Machine Reading Comprehension
To address this problem, we propose RoR, a read-over-read method, which expands the reading field from chunk to document.
CUSTOM: Aspect-Oriented Product Summarization for E-Commerce
To address the problem, we propose CUSTOM, aspect-oriented product summarization for e-commerce, which generates diverse and controllable summaries towards different product aspects.
EviDR: Evidence-Emphasized Discrete Reasoning for Reasoning Machine Reading Comprehension
Reasoning machine reading comprehension (R-MRC) aims to answer complex questions that require discrete reasoning based on text.
Don't Take It Literally: An Edit-Invariant Sequence Loss for Text Generation
Such training objective is sub-optimal when the target sequence is not perfect, e. g., when the target sequence is corrupted with noises, or when only weak sequence supervision is available.
RevCore: Review-augmented Conversational Recommendation
Existing conversational recommendation (CR) systems usually suffer from insufficient item information when conducted on short dialogue history and unfamiliar items.
SGG: Learning to Select, Guide, and Generate for Keyphrase Generation
Keyphrases, that concisely summarize the high-level topics discussed in a document, can be categorized into present keyphrase which explicitly appears in the source text, and absent keyphrase which does not match any contiguous subsequence but is highly semantically related to the source.
Learning to Decouple Relations: Few-Shot Relation Classification with Entity-Guided Attention and Confusion-Aware Training
This paper aims to enhance the few-shot relation classification especially for sentences that jointly describe multiple relations.
Table-to-Text: Describing Table Region with Natural Language
The model maps a row from a table to a continuous vector and then generates a natural language sentence by leveraging the semantics of a table.
Content-Based Table Retrieval for Web Queries
Understanding the connections between unstructured text and semi-structured table is an important yet neglected problem in natural language processing.
Constraint-Based Question Answering with Knowledge Graph
WebQuestions and SimpleQuestions are two benchmark data-sets commonly used in recent knowledge-based question answering (KBQA) work.
