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Loss Functions

1162 directly classified papers

Papers per year

Papers

Less is More: Mitigating Multimodal Hallucination from an EOS Decision Perspective ACL 2024
PCICUNAM at WASSA 2024: Cross-lingual Emotion Detection Task with Hierarchical Classification and Weighted Loss Functions ACL 2024
TueSents at SemEval-2024 Task 8: Predicting the Shift from Human Authorship to Machine-generated Output in a Mixed Text NAACL 2024
Reward Modeling Requires Automatic Adjustment Based on Data Quality EMNLP 2024
Scoring with Confidence? – Exploring High-confidence Scoring for Saving Manual Grading Effort NAACL 2024
Bit_numeval at SemEval-2024 Task 7: Enhance Numerical Sensitivity and Reasoning Completeness for Quantitative Understanding SEMEVAL 2024
Improving Readability Assessment with Ordinal Log-Loss NAACL 2024
Rewarding What Matters: Step-by-Step Reinforcement Learning for Task-Oriented Dialogue EMNLP 2024
Non-contrastive sentence representations via self-supervision NAACL 2024
Dynamic Multi-Reward Weighting for Multi-Style Controllable Generation EMNLP 2024
ROUGE-K: Do Your Summaries Have Keywords? NAACL 2024
Balanced-Wav2Vec: Enhancing Stability and Robustness of Representation Learning Through Sample Reweighting Techniques INTERSPEECH 2024
MaxEnt Loss: Calibrating Graph Neural Networks under Out-of-Distribution Shift (Student Abstract) AAAI 2024
Improving Discriminative Capability of Reward Models in RLHF Using Contrastive Learning EMNLP 2024
ATS: Adaptive Temperature Scaling for Enhancing Out-of-Distribution Detection Methods WACV 2024
Label Alignment Regularization for Distribution Shift JMLR 2024
Improving Factual Consistency in Abstractive Summarization with Sentence Structure Pruning COLING 2024
A Survey of Learning Criteria Going beyond the Usual Risk (Abstract Reprint) AAAI 2024
F2RL: Factuality and Faithfulness Reinforcement Learning Framework for Claim-Guided Evidence-Supported Counterspeech Generation EMNLP 2024
The good, the bad and the ugly sides of data augmentation: An implicit spectral regularization perspective JMLR 2024
Rethinking Discount Regularization: New Interpretations, Unintended Consequences, and Solutions for Regularization in Reinforcement Learning JMLR 2024
Symmetric Q-learning: Reducing Skewness of Bellman Error in Online Reinforcement Learning AAAI 2024
Dropout Regularization Versus l2-Penalization in the Linear Model JMLR 2024
The Role of n-gram Smoothing in the Age of Neural Networks NAACL 2024
Evaluating Generative Language Models in Information Extraction as Subjective Question Correction COLING 2024