GEM 2023 — accepted papers
GEM 2023 is the 2023 edition of the Workshop on Generation, Evaluation and Metrics (GEM), held in Singapore, December 2023 (publisher: Association for Computational Linguistics). The ACL Anthology lists 32 papers of it; our library holds 1 with our summaries. Below: the most cited papers, every accepted paper, and ours with their topics, authors and institutions.
📍 Singapore · 🗓 December 2023
All accepted papers (32)
- A Simple yet Efficient Ensemble Approach for AI-generated Text Detection ↗Harika Abburi, Kalyani Roy, Michael Suesserman et al.
- Adapting Pre-trained Generative Models for Extractive Question Answering ↗Prabir Mallick, Tapas Nayak, Indrajit Bhattacharya
- An Empirical Bayes Framework for Open-Domain Dialogue Generation ↗Jing Yang Lee, Kong Aik Lee, Woon Seng Gan
- Are Large Language Models Reliable Judges? A Study on the Factuality Evaluation Capabilities of LLMs ↗Xue-Yong Fu, Md Tahmid Rahman Laskar, Cheng Chen et al.
- Automatic Evaluation of Generative Models with Instruction Tuning ↗Shuhaib Mehri, Vered Shwartz
- Automatic Reflection Generation for Peer-to-Peer Counseling ↗Emma O'neil, João Sedoc, Diyi Yang et al.
- ChatGPT as a Java Decompiler ↗Bradley Mcdanel, Zhanhao Liu
- Context and Literacy Aware Learnable Metric for Text Simplification ↗Jeongwon Kwak, Hyeryun Park, Kyungmo Kim et al.
- Dialogue Quality and Emotion Annotations for Customer Support Conversations ↗John Mendonca, Patrícia Pereira, Miguel Menezes et al.
- Effective Proxy for Human Labeling: Ensemble Disagreement Scores in Large Language Models for Industrial NLP ↗Wei Du, Laksh Advani, Yashmeet Gambhir et al.
- Elo Uncovered: Robustness and Best Practices in Language Model Evaluation ↗Meriem Boubdir, Edward Kim, Beyza Ermis et al.
- Flesch or Fumble? Evaluating Readability Standard Alignment of Instruction-Tuned Language Models ↗Joseph Marvin Imperial, Harish Tayyar Madabushi
- Formalizing content creation and evaluation methods for AI-generated social media content ↗Christian Jensen, Axel Højmark
- Harnessing the Plug-and-Play Controller by Prompting ↗Hao Wang, Lei Sha
- How well ChatGPT understand Malaysian English? An Evaluation on Named Entity Recognition and Relation ExtractionMohan Raj Chanthran, Lay-Ki Soon, Huey Fang Ong et al.our summary
- Leveraging Large Language Models for Enhanced Product Descriptions in eCommerce ↗Jianghong Zhou, Bo Liu, Jhalak Acharya et al.
- Multi-domain Summarization from Leaderboards to Practice: Re-examining Automatic and Human Evaluation ↗David Demeter, Oshin Agarwal, Simon Ben Igeri et al.
- One-Shot and Few-Shot Exemplification Modeling ↗John Harvill, Hee Suk Yoon, Eunseop Yoon et al.
- PersonalityChat: Conversation Distillation for Personalized Dialog Modeling with Facts and Traits ↗Ehsan Lotfi, Maxime De Bruyn, Jeska Buhmann et al.
- Post Turing: Mapping the landscape of LLM Evaluation ↗Alexey Tikhonov, Ivan P. Yamshchikov
- Predicting Question-Answering Performance of Large Language Models through Semantic Consistency ↗Ella Rabinovich, Samuel Ackerman, Orna Raz et al.
- QAMPARI: A Benchmark for Open-domain Questions with Many Answers ↗Samuel Amouyal, Tomer Wolfson, Ohad Rubin et al.
- RankAug: Augmented data ranking for text classification ↗Tiasa Roy, Priyam Basu
- Separating form and meaning: Using self-consistency to quantify task understanding across multiple senses ↗Xenia Ohmer, Elia Bruni, Dieuwke Hupkes
See all 32 papers in GEM 2023 — accepted papers →
Papers with our summary in our library (1)
- How well ChatGPT understand Malaysian English? An Evaluation on Named Entity Recognition and Relation ExtractionWorkshop on Generation, Evaluation and Metrics (GEM)Mohan Raj Chanthran, Lay-Ki Soon, Huey Fang Ong, et al.2023 · 2 citations
Top topics
Named entity recognition (1)Information extraction (1)Evaluation & benchmarks (1)English (1)
Fields
Arts and Humanities (1)Computer Science (1)
Top authors
🧑🔬Bhawani Selvaretnam1 work here · 2 citations🧑🔬Huey Fang Ong1 work here · 2 citations🧑🔬Lay-Ki Soon1 work here · 2 citations🧑🔬Mohan Raj Chanthran1 work here · 2 citations
Top institutions
This page in Markdown → https://md.research.elamur.ai/free/en/venues/gem/2023/