Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Building Watson: An Overview of the DeepQA Project
2010789 citationsEric Nyberg, Nico Schlaefer et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Eric Nyberg's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Eric Nyberg with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eric Nyberg more than expected).
This network shows the impact of papers produced by Eric Nyberg. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Eric Nyberg. The network helps show where Eric Nyberg may publish in the future.
Co-authorship network of co-authors of Eric Nyberg
This figure shows the co-authorship network connecting the top 25 collaborators of Eric Nyberg.
A scholar is included among the top collaborators of Eric Nyberg based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Eric Nyberg. Eric Nyberg is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
All Works
20 of 20 papers shown
1.
Wang, Di & Eric Nyberg. (2017). CMU OAQA at TREC 2017 LiveQA: A Neural Dual Entailment Approach for Question Paraphrase Identification.. Text REtrieval Conference.7 indexed citations
2.
Wang, Di, Leonid Boytsov, Jun Araki, et al.. (2014). CMU Multiple-choice Question Answering System at NTCIR-11 QA-Lab. NTCIR.2 indexed citations
3.
Nyberg, Eric, et al.. (2013). Building Optimal Question Answering System Automatically using Configuration Space Exploration (CSE) for QA4MRE 2013 Tasks.. CLEF (Working Notes).4 indexed citations
4.
Nyberg, Eric, et al.. (2011). Assessing Benefit from Feature Feedback in Active Learning for Text Classification. 106–114.1 indexed citations
5.
Mayfield, Elijah, et al.. (2010). Sentiment Classification using Automatically Extracted Subgraph Features. North American Chapter of the Association for Computational Linguistics. 131–139.23 indexed citations
6.
Lao, Ni, et al.. (2008). Complex Cross-lingual Question Answering as a Sequential Classification and Multi-Document Summarization Task. NTCIR.4 indexed citations
7.
Nyberg, Eric, et al.. (2008). Integrating a Natural Language Message Pre-Processor with UIMA.1 indexed citations
8.
Lao, Ni, et al.. (2008). Query Expansion and Machine Translation for Robust Cross-Lingual Information Retrieval. NTCIR.4 indexed citations
9.
Mitamura, Teruko, Eric Nyberg, Tsuneaki Kato, et al.. (2008). Overview of the NTCIR-7 ACLIA Tasks: Advanced Cross-Lingual Information Access. NTCIR. 15–24.22 indexed citations
10.
Schlaefer, Nico, et al.. (2007). SEMANTIC EXTENSIONS OF THE EPHYRA QA SYSTEM FOR TREC 2007. Text REtrieval Conference.34 indexed citations
11.
Mitamura, Teruko, et al.. (2007). JAVELIN III: Cross-Lingual Question Answering from Japanese and Chinese Documents. NTCIR.10 indexed citations
12.
Mitamura, Teruko, et al.. (2007). Language-independent Probabilistic Answer Ranking for Question Answering. Meeting of the Association for Computational Linguistics. 784–791.13 indexed citations
13.
Si, Luo, et al.. (2007). A Probabilistic Framework for Answer Selection in Question Answering. North American Chapter of the Association for Computational Linguistics. 524–531.24 indexed citations
14.
Nyberg, Eric, et al.. (2006). Evaluation for Scenario Question Answering Systems.. Language Resources and Evaluation. 1536–1541.5 indexed citations
15.
Nyberg, Eric, et al.. (2006). Exploiting Multiple Semantic Resources for Answer Selection. Language Resources and Evaluation. 1139–1142.5 indexed citations
16.
Nyberg, Eric, et al.. (2005). JAVELIN I and II Systems at TREC 2005. Text REtrieval Conference.20 indexed citations
17.
Nyberg, Eric, et al.. (2004). An Information Repository Model for Advanced Question Answering Systems. Language Resources and Evaluation.1 indexed citations
18.
Nyberg, Eric, et al.. (2002). DialogXML: extending VoiceXML for dynamic dialog management. 298–302.7 indexed citations
19.
Mitamura, Teruko, Eric Nyberg, & Jaime Carbonell. (1994). KANT: Knowledge-Based, Accurate Natural Language Translation. Conference of the Association for Machine Translation in the Americas.1 indexed citations
20.
Nirenburg, Sergei, Victor Lesser, & Eric Nyberg. (1989). Controlling a language generation planner. International Joint Conference on Artificial Intelligence. 1524–1530.26 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.