Papers
214 papers found
Protecting Users From Themselves: Safeguarding Contextual Privacy in Interactions with Conversational Agents
Ivoline C. Ngong, Swanand Ravindra Kadhe, Hao Wang et al.
“The Facts Speak for Themselves”: GPT and Fallacy Classification
Erisa Bytyqi, Annette Hautli-Janisz
CHILL at SemEval-2025 Task 2: You Can’t Just Throw Entities and Hope—Make Your LLM to Get Them Right
Jaebok Lee, Yonghyun Ryu, Seongmin Park et al.
If you’ve seen some, you’ve seen them all: Identifying variants of multiword expressions
Caroline Pasquer, Agata Savary, Carlos Ramisch et al.
ApplicaAI at SemEval-2020 Task 11: On RoBERTa-CRF, Span CLS and Whether Self-Training Helps Them
Dawid Jurkiewicz, Łukasz Borchmann, Izabela Kosmala et al.
Benchmark for Research Theme Classification of Scholarly Documents
Óscar E. Mendoza, Wojciech Kusa, Alaa El-Ebshihy et al.
Constructions Are So Difficult That Even Large Language Models Get Them Right for the Wrong Reasons
Shijia Zhou, Leonie Weissweiler, Taiqi He et al.
Ethical Reasoning and Moral Value Alignment of LLMs Depend on the Language We Prompt Them in
Utkarsh Agarwal, Kumar Tanmay, Aditi Khandelwal et al.
Interpreting Themes from Educational Stories
Yigeng Zhang, Fabio Gonzalez, Thamar Solorio
OOVs in the Spotlight: How to Inflect Them?
Tomáš Sourada, Jana Straková, Rudolf Rosa
Cheap Talk: Topic Analysis of CSR Themes on Corporate Twitter
Nile Phillips, Sathvika Anand, Michelle Lum et al.
Shared Task for Cross-lingual Classification of Corporate Social Responsibility (CSR) Themes and Topics
Yola Nayekoo, Sophia Katrenko, Veronique Hoste et al.
Advancing CSR Theme and Topic Classification: LLMs and Training Enhancement Insights
Jens Van Nooten, Andriy Kosar
Predicting Fine-tuned Performance on Larger Datasets Before Creating Them
Toshiki Kuramoto, Jun Suzuki
Planting trees in graphs, and finding them back
Laurent Massoulié, Ludovic Stephan, Don Towsley
Understanding Deep Image Representations by Inverting Them
Aravindh Mahendran, Andrea Vedaldi
Disentangling Factors of Variation by Mixing Them
Qiyang Hu, Attila Szabó, Tiziano Portenier et al.
Answer Them All! Toward Universal Visual Question Answering Models
Robik Shrestha, Kushal Kafle, Christopher Kanan
Fantastic Answers and Where to Find Them: Immersive Question-Directed Visual Attention
Ming Jiang, Shi Chen, Jinhui Yang et al.
Effectively Unbiased FID and Inception Score and Where to Find Them
Min Jin Chong, David Forsyth
Roses Are Red, Violets Are Blue... but Should VQA Expect Them To?
Corentin Kervadec, Grigory Antipov, Moez Baccouche et al.
Learning Accurate Dense Correspondences and When To Trust Them
Prune Truong, Martin Danelljan, Luc Van Gool et al.
Deep 3D-to-2D Watermarking: Embedding Messages in 3D Meshes and Extracting Them From 2D Renderings
Innfarn Yoo, Huiwen Chang, Xiyang Luo et al.
ImageBind: One Embedding Space To Bind Them All
Rohit Girdhar, Alaaeldin El-Nouby, Zhuang Liu et al.