Saved in:
| Main Authors: | Ilić, David, Gignac, Gilles E. |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2310.11616 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Integration of cognitive tasks into artificial general intelligence test for large models
by: Qu, Youzhi, et al.
Published: (2024)
by: Qu, Youzhi, et al.
Published: (2024)
ZNO-Eval: Benchmarking reasoning capabilities of large language models in Ukrainian
by: Syromiatnikov, Mykyta, et al.
Published: (2025)
by: Syromiatnikov, Mykyta, et al.
Published: (2025)
The 20 questions game to distinguish large language models
by: Richardeau, Gurvan, et al.
Published: (2024)
by: Richardeau, Gurvan, et al.
Published: (2024)
An artificial intelligence framework for end-to-end rare disease phenotyping from clinical notes using large language models
by: Shyr, Cathy, et al.
Published: (2026)
by: Shyr, Cathy, et al.
Published: (2026)
ClinicalGPT-R1: Pushing reasoning capability of generalist disease diagnosis with large language model
by: Lan, Wuyang, et al.
Published: (2025)
by: Lan, Wuyang, et al.
Published: (2025)
Disentangling generalization and memorization in large language models using chess
by: Pleiss, Leonard S., et al.
Published: (2026)
by: Pleiss, Leonard S., et al.
Published: (2026)
Auxiliary task demands mask the capabilities of smaller language models
by: Hu, Jennifer, et al.
Published: (2024)
by: Hu, Jennifer, et al.
Published: (2024)
Fine-tuning large language models for domain adaptation: Exploration of training strategies, scaling, model merging and synergistic capabilities
by: Lu, Wei, et al.
Published: (2024)
by: Lu, Wei, et al.
Published: (2024)
Dissociating language and thought in large language models
by: Mahowald, Kyle, et al.
Published: (2023)
by: Mahowald, Kyle, et al.
Published: (2023)
Post-training makes large language models less human-like
by: Binz, Marcel, et al.
Published: (2026)
by: Binz, Marcel, et al.
Published: (2026)
MindScope: Exploring cognitive biases in large language models through Multi-Agent Systems
by: Xie, Zhentao, et al.
Published: (2024)
by: Xie, Zhentao, et al.
Published: (2024)
Quantifying artificial intelligence through algorithmic generalization
by: Ito, Takuya, et al.
Published: (2024)
by: Ito, Takuya, et al.
Published: (2024)
A technical curriculum on language-oriented artificial intelligence in translation and specialised communication
by: Krüger, Ralph
Published: (2026)
by: Krüger, Ralph
Published: (2026)
Evidence from counterfactual tasks supports emergent analogical reasoning in large language models
by: Webb, Taylor, et al.
Published: (2024)
by: Webb, Taylor, et al.
Published: (2024)
Bringing order into the realm of Transformer-based language models for artificial intelligence and law
by: Greco, Candida M., et al.
Published: (2023)
by: Greco, Candida M., et al.
Published: (2023)
On the attribution of confidence to large language models
by: Keeling, Geoff, et al.
Published: (2024)
by: Keeling, Geoff, et al.
Published: (2024)
Do explanations generalize across large reasoning models?
by: Pal, Koyena, et al.
Published: (2026)
by: Pal, Koyena, et al.
Published: (2026)
Representation in large language models
by: Yetman, Cameron
Published: (2025)
by: Yetman, Cameron
Published: (2025)
Alignment faking in large language models
by: Greenblatt, Ryan, et al.
Published: (2024)
by: Greenblatt, Ryan, et al.
Published: (2024)
Evidence of a log scaling law for political persuasion with large language models
by: Hackenburg, Kobi, et al.
Published: (2024)
by: Hackenburg, Kobi, et al.
Published: (2024)
Failure of contextual invariance in large language models
by: Kumar, Sagar, et al.
Published: (2026)
by: Kumar, Sagar, et al.
Published: (2026)
Can large language models build causal graphs?
by: Long, Stephanie, et al.
Published: (2023)
by: Long, Stephanie, et al.
Published: (2023)
Response: Emergent analogical reasoning in large language models
by: Hodel, Damian, et al.
Published: (2023)
by: Hodel, Damian, et al.
Published: (2023)
Quantifying non deterministic drift in large language models
by: Nicholson, Claire
Published: (2026)
by: Nicholson, Claire
Published: (2026)
Multi-round jailbreak attack on large language models
by: Zhou, Yihua, et al.
Published: (2024)
by: Zhou, Yihua, et al.
Published: (2024)
AI-AI Bias: large language models favor communications generated by large language models
by: Laurito, Walter, et al.
Published: (2024)
by: Laurito, Walter, et al.
Published: (2024)
Optimizing watermarks for large language models
by: Wouters, Bram
Published: (2023)
by: Wouters, Bram
Published: (2023)
A survey of textual cyber abuse detection using cutting-edge language models and large language models
by: Diaz-Garcia, Jose A., et al.
Published: (2025)
by: Diaz-Garcia, Jose A., et al.
Published: (2025)
Strong and weak alignment of large language models with human values
by: Khamassi, Mehdi, et al.
Published: (2024)
by: Khamassi, Mehdi, et al.
Published: (2024)
Streamlining evidence based clinical recommendations with large language models
by: Li, Dubai, et al.
Published: (2025)
by: Li, Dubai, et al.
Published: (2025)
Correcting misinformation on social media with a large language model
by: Zhou, Xinyi, et al.
Published: (2024)
by: Zhou, Xinyi, et al.
Published: (2024)
Re-evaluating Theory of Mind evaluation in large language models
by: Hu, Jennifer, et al.
Published: (2025)
by: Hu, Jennifer, et al.
Published: (2025)
A review on the use of large language models as virtual tutors
by: García-Méndez, Silvia, et al.
Published: (2024)
by: García-Méndez, Silvia, et al.
Published: (2024)
Evaluating large language models in medical applications: a survey
by: Chen, Xiaolan, et al.
Published: (2024)
by: Chen, Xiaolan, et al.
Published: (2024)
MathDivide: Improved mathematical reasoning by large language models
by: Srivastava, Saksham Sahai, et al.
Published: (2024)
by: Srivastava, Saksham Sahai, et al.
Published: (2024)
Medical large language models are easily distracted
by: Vishwanath, Krithik, et al.
Published: (2025)
by: Vishwanath, Krithik, et al.
Published: (2025)
A general tensor-structured compression scheme for efficient large language models
by: Lu, Ying, et al.
Published: (2026)
by: Lu, Ying, et al.
Published: (2026)
Uncovering inequalities in new knowledge learning by large language models across different languages
by: Wang, Chenglong, et al.
Published: (2025)
by: Wang, Chenglong, et al.
Published: (2025)
The use of large language models to enhance cancer clinical trial educational materials
by: Gao, Mingye, et al.
Published: (2024)
by: Gao, Mingye, et al.
Published: (2024)
Large language models show fragile cognitive reasoning about human emotions
by: Bhattacharyya, Sree, et al.
Published: (2025)
by: Bhattacharyya, Sree, et al.
Published: (2025)
Similar Items
-
Integration of cognitive tasks into artificial general intelligence test for large models
by: Qu, Youzhi, et al.
Published: (2024) -
ZNO-Eval: Benchmarking reasoning capabilities of large language models in Ukrainian
by: Syromiatnikov, Mykyta, et al.
Published: (2025) -
The 20 questions game to distinguish large language models
by: Richardeau, Gurvan, et al.
Published: (2024) -
An artificial intelligence framework for end-to-end rare disease phenotyping from clinical notes using large language models
by: Shyr, Cathy, et al.
Published: (2026) -
ClinicalGPT-R1: Pushing reasoning capability of generalist disease diagnosis with large language model
by: Lan, Wuyang, et al.
Published: (2025)