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Found 21 papers, 15 papers with code
Localizing Factual Inconsistencies in Attributable Text Generation
There has been an increasing interest in detecting hallucinations in model-generated texts, both manually and automatically, at varying levels of granularity.
Explicating the Implicit: Argument Detection Beyond Sentence Boundaries
Detecting semantic arguments of a predicate word has been conventionally modeled as a sentence-level task.
SEAM: A Stochastic Benchmark for Multi-Document Tasks
Various tasks, such as summarization, multi-hop question answering, or coreference resolution, are naturally phrased over collections of real-world documents.
Can Few-shot Work in Long-Context? Recycling the Context to Generate Demonstrations
Despite recent advancements in Large Language Models (LLMs), their performance on tasks involving long contexts remains sub-optimal.
Attribute First, then Generate: Locally-attributable Grounded Text Generation
Recent efforts to address hallucinations in Large Language Models (LLMs) have focused on attributed text generation, which supplements generated texts with citations of supporting sources for post-generation fact-checking and corrections.
CHAMP: Efficient Annotation and Consolidation of Cluster Hierarchies
Various NLP tasks require a complex hierarchical structure over nodes, where each node is a cluster of items.
coreference-resolution
Cross Document Coreference Resolution
From Key Points to Key Point Hierarchy: Structured and Expressive Opinion Summarization
Key Point Analysis (KPA) has been recently proposed for deriving fine-grained insights from collections of textual comments.
Evaluating and Improving the Coreference Capabilities of Machine Translation Models
Machine translation (MT) requires a wide range of linguistic capabilities, which current end-to-end models are expected to learn implicitly by observing aligned sentences in bilingual corpora.
How "Multi" is Multi-Document Summarization?
To that end, we propose an automated measure for evaluating the degree to which a summary is ``disperse'', in the sense of the number of source documents needed to cover its content.
F-coref: Fast, Accurate and Easy to Use Coreference Resolution
We introduce fastcoref, a python package for fast, accurate, and easy-to-use English coreference resolution.
LingMess: Linguistically Informed Multi Expert Scorers for Coreference Resolution
While coreference resolution typically involves various linguistic challenges, recent models are based on a single pairwise scorer for all types of pairs.
Ranked #5 on
Coreference Resolution
on OntoNotes
iFacetSum: Coreference-based Interactive Faceted Summarization for Multi-Document Exploration
We introduce iFacetSum, a web application for exploring topical document sets.
Realistic Evaluation Principles for Cross-document Coreference Resolution
We point out that common evaluation practices for cross-document coreference resolution have been unrealistically permissive in their assumed settings, yielding inflated results.
coreference-resolution
Cross Document Coreference Resolution
Cross-document Coreference Resolution over Predicted Mentions
Here, we introduce the first end-to-end model for CD coreference resolution from raw text, which extends the prominent model for within-document coreference to the CD setting.
coreference-resolution
Cross Document Coreference Resolution
SciCo: Hierarchical Cross-Document Coreference for Scientific Concepts
Determining coreference of concept mentions across multiple documents is a fundamental task in natural language understanding.
coreference-resolution
Cross Document Coreference Resolution
+1
WEC: Deriving a Large-scale Cross-document Event Coreference dataset from Wikipedia
To complement these resources and enhance future research, we present Wikipedia Event Coreference (WEC), an efficient methodology for gathering a large-scale dataset for cross-document event coreference from Wikipedia, where coreference links are not restricted within predefined topics.
CD\^2CR: Co-reference resolution across documents and domains
Cross-document co-reference resolution (CDCR) is the task of identifying and linking mentions to entities and concepts across many text documents.
CD2CR: Co-reference Resolution Across Documents and Domains
Cross-document co-reference resolution (CDCR) is the task of identifying and linking mentions to entities and concepts across many text documents.
CDLM: Cross-Document Language Modeling
We introduce a new pretraining approach geared for multi-document language modeling, incorporating two key ideas into the masked language modeling self-supervised objective.
Ranked #1 on
Citation Recommendation
on AAN test
CoRefi: A Crowd Sourcing Suite for Coreference Annotation
Coreference annotation is an important, yet expensive and time consuming, task, which often involved expert annotators trained on complex decision guidelines.
Streamlining Cross-Document Coreference Resolution: Evaluation and Modeling
Recent evaluation protocols for Cross-document (CD) coreference resolution have often been inconsistent or lenient, leading to incomparable results across works and overestimation of performance.
coreference-resolution
Cross Document Coreference Resolution
+2
