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Found 17 papers, 6 papers with code
A Neural Graph-based Local Coherence Model
Entity grids and entity graphs are two frameworks for modeling local coherence.
Python Code Generation by Asking Clarification Questions
We hypothesize that the under-specification of a natural language description can be resolved by asking clarification questions.
The Devil is in the Details: On Models and Training Regimes for Few-Shot Intent Classification
First, the unexplored combination of the cross-encoder architecture (with parameterized similarity scoring function) and episodic meta-learning consistently yields the best FSIC performance.
ArgSciChat: A Dataset for Argumentative Dialogues on Scientific Papers
The applications of conversational agents for scientific disciplines (as expert domains) are understudied due to the lack of dialogue data to train such agents.
Ranked #1 on
Fact Selection
on ArgSciChat
Improving Factual Consistency Between a Response and Persona Facts
Neural models for response generation produce responses that are semantically plausible but not necessarily factually consistent with facts describing the speaker's persona.
When is ACL's Deadline? A Scientific Conversational Agent
Our conversational agent UKP-ATHENA assists NLP researchers in finding and exploring scientific literature, identifying relevant authors, planning or post-processing conference visits, and preparing paper submissions using a unified interface based on natural language inputs and responses.
Dialogue Coherence Assessment Without Explicit Dialogue Act Labels
Recent dialogue coherence models use the coherence features designed for monologue texts, e. g. nominal entities, to represent utterances and then explicitly augment them with dialogue-relevant features, e. g., dialogue act labels.
Reward Learning for Efficient Reinforcement Learning in Extractive Document Summarisation
The predominant RL paradigm for summarisation learns a cross-input policy, which requires considerable time, data and parameter tuning due to the huge search spaces and the delayed rewards.
Text Processing Like Humans Do: Visually Attacking and Shielding NLP Systems
Visual modifications to text are often used to obfuscate offensive comments in social media (e. g., "! d10t") or as a writing style ("1337" in "leet speak"), among other scenarios.
A Neural Local Coherence Model for Text Quality Assessment
We propose a local coherence model that captures the flow of what semantically connects adjacent sentences in a text.
Using a Graph-based Coherence Model in Document-Level Machine Translation
Although coherence is an important aspect of any text generation system, it has received little attention in the context of machine translation (MT) so far.
