Papers
MIL-Decoding: Detoxifying Language Models at Token-Level via Multiple Instance Learning
Xu Zhang, Xiaojun Wan
Minanto at SemEval-2023 Task 2: Fine-tuning XLM-RoBERTa for Named Entity Recognition on English Data
Antonia Höfer, Mina Mottahedin
MIND at SemEval-2023 Task 11: From Uncertain Predictions to Subjective Disagreement
Giulia Rizzi, Alessandro Astorino, Daniel Scalena et al.
Minding Language Models’ (Lack of) Theory of Mind: A Plug-and-Play Multi-Character Belief Tracker
Melanie Sclar, Sachin Kumar, Peter West et al.
Mind the Biases: Quantifying Cognitive Biases in Language Model Prompting
Ruixi Lin, Hwee Tou Ng
Mind the Gap between the Application Track and the Real World
Ananya Ganesh, Jie Cao, E. Margaret Perkoff et al.
Mini-Model Adaptation: Efficiently Extending Pretrained Models to New Languages via Aligned Shallow Training
Kelly Marchisio, Patrick Lewis, Yihong Chen et al.
MIReAD: Simple Method for Learning High-quality Representations from Scientific Documents
Anastasiia Razdaibiedina, Aleksandr Brechalov
MIR-GAN: Refining Frame-Level Modality-Invariant Representations with Adversarial Network for Audio-Visual Speech Recognition
Yuchen Hu, Chen Chen, Ruizhe Li et al.
MISGENDERED: Limits of Large Language Models in Understanding Pronouns
Tamanna Hossain, Sunipa Dev, Sameer Singh
Misleading Relation Classifiers by Substituting Words in Texts
Tian Jiang, Yunqi Liu, Yan Feng et al.
MISMATCH: Fine-grained Evaluation of Machine-generated Text with Mismatch Error Types
Keerthiram Murugesan, Sarathkrishna Swaminathan, Soham Dan et al.
Mitigating Label Biases for In-context Learning
Yu Fei, Yifan Hou, Zeming Chen et al.
Mitigating the Burden of Redundant Datasets via Batch-Wise Unique Samples and Frequency-Aware Losses
Donato Crisostomi, Andrea Caciolai, Alessandro Pedrani et al.
MixCE: Training Autoregressive Language Models by Mixing Forward and Reverse Cross-Entropies
Shiyue Zhang, Shijie Wu, Ozan Irsoy et al.
Mixed Orthographic/Phonemic Language Modeling: Beyond Orthographically Restricted Transformers (BORT)
Robert C. Gale, Alexandra C. Salem, Gerasimos Fergadiotis et al.
MixPAVE: Mix-Prompt Tuning for Few-shot Product Attribute Value Extraction
Li Yang, Qifan Wang, Jingang Wang et al.
Mixture-of-Domain-Adapters: Decoupling and Injecting Domain Knowledge to Pre-trained Language Models’ Memories
Shizhe Diao, Tianyang Xu, Ruijia Xu et al.
MLlab4CS at SemEval-2023 Task 2: Named Entity Recognition in Low-resource Language Bangla Using Multilingual Language Models
Shrimon Mukherjee, Madhusudan Ghosh, Girish et al.
ML-LMCL: Mutual Learning and Large-Margin Contrastive Learning for Improving ASR Robustness in Spoken Language Understanding
Xuxin Cheng, Bowen Cao, Qichen Ye et al.
ML Mob at SemEval-2023 Task 1: Probing CLIP on Visual Word-Sense Disambiguation
Clifton Poth, Martin Hentschel, Tobias Werner et al.
ML Mob at SemEval-2023 Task 5: “Breaking News: Our Semi-Supervised and Multi-Task Learning Approach Spoils Clickbait”
Hannah Sterz, Leonard Bongard, Tobias Werner et al.
MLModeler5 at SemEval-2023 Task 3: Detecting the Category and the Framing Techniques in Online News in a Multi-lingual Setup
Arjun Khanchandani, Nitansh Jain, Jatin Bedi