Saved in:
| Main Authors: | Fleisig, Eve, Orlikowski, Matthias, Cimiano, Philipp, Klein, Dan |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2509.08217 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
When the Majority is Wrong: Modeling Annotator Disagreement for Subjective Tasks
by: Fleisig, Eve, et al.
Published: (2023)
by: Fleisig, Eve, et al.
Published: (2023)
Architectural Sweet Spots for Modeling Human Label Variation by the Example of Argument Quality: It's Best to Relate Perspectives!
by: Heinisch, Philipp, et al.
Published: (2023)
by: Heinisch, Philipp, et al.
Published: (2023)
Ghostbuster: Detecting Text Ghostwritten by Large Language Models
by: Verma, Vivek, et al.
Published: (2023)
by: Verma, Vivek, et al.
Published: (2023)
The Ecological Fallacy in Annotation: Modelling Human Label Variation goes beyond Sociodemographics
by: Orlikowski, Matthias, et al.
Published: (2023)
by: Orlikowski, Matthias, et al.
Published: (2023)
The Perspectivist Paradigm Shift: Assumptions and Challenges of Capturing Human Labels
by: Fleisig, Eve, et al.
Published: (2024)
by: Fleisig, Eve, et al.
Published: (2024)
CompoST: A Benchmark for Analyzing the Ability of LLMs To Compositionally Interpret Questions in a QALD Setting
by: Schmidt, David Maria, et al.
Published: (2025)
by: Schmidt, David Maria, et al.
Published: (2025)
Mapping Social Choice Theory to RLHF
by: Dai, Jessica, et al.
Published: (2024)
by: Dai, Jessica, et al.
Published: (2024)
From Argumentation to Deliberation: Perspectivized Stance Vectors for Fine-grained (Dis)agreement Analysis
by: Plenz, Moritz, et al.
Published: (2025)
by: Plenz, Moritz, et al.
Published: (2025)
PluriHarms: Benchmarking the Full Spectrum of Human Judgments on AI Harm
by: Li, Jing-Jing, et al.
Published: (2026)
by: Li, Jing-Jing, et al.
Published: (2026)
Lexicalization Is All You Need: Examining the Impact of Lexical Knowledge in a Compositional QALD System
by: Schmidt, David Maria, et al.
Published: (2024)
by: Schmidt, David Maria, et al.
Published: (2024)
Conditional Semi-Supervised Data Augmentation for Spam Message Detection with Low Resource Data
by: Nuha, Ulin, et al.
Published: (2024)
by: Nuha, Ulin, et al.
Published: (2024)
GCC-Spam: Spam Detection via GAN, Contrastive Learning, and Character Similarity Networks
by: Wang, Zhijie, et al.
Published: (2025)
by: Wang, Zhijie, et al.
Published: (2025)
AI, Take the Wheel: What Drives Delegation and Trust in Human-Computer Cooperative Question Answering?
by: Gor, Maharshi, et al.
Published: (2026)
by: Gor, Maharshi, et al.
Published: (2026)
Beyond Demographics: Fine-tuning Large Language Models to Predict Individuals' Subjective Text Perceptions
by: Orlikowski, Matthias, et al.
Published: (2025)
by: Orlikowski, Matthias, et al.
Published: (2025)
Evaluating the Performance of ChatGPT for Spam Email Detection
by: Si, Shijing, et al.
Published: (2024)
by: Si, Shijing, et al.
Published: (2024)
Linguistic Bias in ChatGPT: Language Models Reinforce Dialect Discrimination
by: Fleisig, Eve, et al.
Published: (2024)
by: Fleisig, Eve, et al.
Published: (2024)
SmolKalam: Ensemble Quality-Filtered Translation at Scale for High Quality Arabic Post-Training Data
by: Alrashed, Sultan, et al.
Published: (2025)
by: Alrashed, Sultan, et al.
Published: (2025)
Accurate and Data-Efficient Toxicity Prediction when Annotators Disagree
by: Jaggi, Harbani, et al.
Published: (2024)
by: Jaggi, Harbani, et al.
Published: (2024)
American Sign Language Handshapes Reflect Pressures for Communicative Efficiency
by: Yin, Kayo, et al.
Published: (2024)
by: Yin, Kayo, et al.
Published: (2024)
THOUGHTSCULPT: Reasoning with Intermediate Revision and Search
by: Chi, Yizhou, et al.
Published: (2024)
by: Chi, Yizhou, et al.
Published: (2024)
SMS Spam Detection and Classification to Combat Abuse in Telephone Networks Using Natural Language Processing
by: Oyeyemi, Dare Azeez, et al.
Published: (2024)
by: Oyeyemi, Dare Azeez, et al.
Published: (2024)
Zero-Shot Spam Email Classification Using Pre-trained Large Language Models
by: Rojas-Galeano, Sergio
Published: (2024)
by: Rojas-Galeano, Sergio
Published: (2024)
High-Quality Data Augmentation for Low-Resource NMT: Combining a Translation Memory, a GAN Generator, and Filtering
by: Liu, Hengjie, et al.
Published: (2024)
by: Liu, Hengjie, et al.
Published: (2024)
Judging Quality Across Languages: A Multilingual Approach to Pretraining Data Filtering with Language Models
by: Ali, Mehdi, et al.
Published: (2025)
by: Ali, Mehdi, et al.
Published: (2025)
Label Distribution Learning-Enhanced Dual-KNN for Text Classification
by: Yuan, Bo, et al.
Published: (2025)
by: Yuan, Bo, et al.
Published: (2025)
Filtered Reasoning Score: Evaluating Reasoning Quality on a Model's Most-Confident Traces
by: Pathak, Manas, et al.
Published: (2026)
by: Pathak, Manas, et al.
Published: (2026)
RLCD: Reinforcement Learning from Contrastive Distillation for Language Model Alignment
by: Yang, Kevin, et al.
Published: (2023)
by: Yang, Kevin, et al.
Published: (2023)
Improving Neural Topic Modeling with Semantically-Grounded Soft Label Distributions
by: Li, Raymond, et al.
Published: (2026)
by: Li, Raymond, et al.
Published: (2026)
Balanced Data Sampling for Language Model Training with Clustering
by: Shao, Yunfan, et al.
Published: (2024)
by: Shao, Yunfan, et al.
Published: (2024)
How LLMs Distort Our Written Language
by: Abdulhai, Marwa, et al.
Published: (2026)
by: Abdulhai, Marwa, et al.
Published: (2026)
First Tragedy, then Parse: History Repeats Itself in the New Era of Large Language Models
by: Saphra, Naomi, et al.
Published: (2023)
by: Saphra, Naomi, et al.
Published: (2023)
HQA-Attack: Toward High Quality Black-Box Hard-Label Adversarial Attack on Text
by: Liu, Han, et al.
Published: (2024)
by: Liu, Han, et al.
Published: (2024)
From Noise to Signal to Selbstzweck: Reframing Human Label Variation in the Era of Post-training in NLP
by: Xu, Shanshan, et al.
Published: (2025)
by: Xu, Shanshan, et al.
Published: (2025)
Signature vs. Substance: Evaluating the Balance of Adversarial Resistance and Linguistic Quality in Watermarking Large Language Models
by: Guo, William, et al.
Published: (2025)
by: Guo, William, et al.
Published: (2025)
TrustDataFilter:Leveraging Trusted Knowledge Base Data for More Effective Filtering of Unknown Information
by: Zhang, Jinghong, et al.
Published: (2025)
by: Zhang, Jinghong, et al.
Published: (2025)
Rethinking KenLM: Good and Bad Model Ensembles for Efficient Text Quality Filtering in Large Web Corpora
by: Kim, Yungi, et al.
Published: (2024)
by: Kim, Yungi, et al.
Published: (2024)
What do language models model? Transformers, automata, and the format of thought
by: Klein, Colin
Published: (2025)
by: Klein, Colin
Published: (2025)
CLARINET: Augmenting Language Models to Ask Clarification Questions for Retrieval
by: Chi, Yizhou, et al.
Published: (2024)
by: Chi, Yizhou, et al.
Published: (2024)
Explaining Datasets in Words: Statistical Models with Natural Language Parameters
by: Zhong, Ruiqi, et al.
Published: (2024)
by: Zhong, Ruiqi, et al.
Published: (2024)
Discovering Latent Knowledge in Language Models Without Supervision
by: Burns, Collin, et al.
Published: (2022)
by: Burns, Collin, et al.
Published: (2022)
Similar Items
-
When the Majority is Wrong: Modeling Annotator Disagreement for Subjective Tasks
by: Fleisig, Eve, et al.
Published: (2023) -
Architectural Sweet Spots for Modeling Human Label Variation by the Example of Argument Quality: It's Best to Relate Perspectives!
by: Heinisch, Philipp, et al.
Published: (2023) -
Ghostbuster: Detecting Text Ghostwritten by Large Language Models
by: Verma, Vivek, et al.
Published: (2023) -
The Ecological Fallacy in Annotation: Modelling Human Label Variation goes beyond Sociodemographics
by: Orlikowski, Matthias, et al.
Published: (2023) -
The Perspectivist Paradigm Shift: Assumptions and Challenges of Capturing Human Labels
by: Fleisig, Eve, et al.
Published: (2024)