Copertina

Unveiling Imitation Learning: Exploring the Impact of Data Falsity to Large Language Model

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autore principale:	Cho, Hyunsoo
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Computation and Language Artificial Intelligence Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Instruction Tuning with Human Curriculum
di: Lee, Bruce W., et al.
Pubblicazione: (2023)

Unveiling and Addressing Pseudo Forgetting in Large Language Models
di: Sun, Huashan, et al.
Pubblicazione: (2024)

Revisiting In-context Learning Inference Circuit in Large Language Models
di: Cho, Hakaze, et al.
Pubblicazione: (2024)

Breach in the Shield: Unveiling the Vulnerabilities of Large Language Models
di: Dai, Runpeng, et al.
Pubblicazione: (2025)

Unveiling Causal Reasoning in Large Language Models: Reality or Mirage?
di: Chi, Haoang, et al.
Pubblicazione: (2025)

Imitating Language via Scalable Inverse Reinforcement Learning
di: Wulfmeier, Markus, et al.
Pubblicazione: (2024)

Negation Blindness in Large Language Models: Unveiling the NO Syndrome in Image Generation
di: Nadeem, Mohammad, et al.
Pubblicazione: (2024)

DIDS: Domain Impact-aware Data Sampling for Large Language Model Training
di: Shi, Weijie, et al.
Pubblicazione: (2025)

Large Language Models Explore by Latent Distilling
di: Zeng, Yuanhao, et al.
Pubblicazione: (2026)

ALPINE: Unveiling the Planning Capability of Autoregressive Learning in Language Models
di: Wang, Siwei, et al.
Pubblicazione: (2024)

Critique of Impure Reason: Unveiling the reasoning behaviour of medical Large Language Models
di: Sim, Shamus, et al.
Pubblicazione: (2024)

Unveiling Narrative Reasoning Limits of Large Language Models with Trope in Movie Synopses
di: Su, Hung-Ting, et al.
Pubblicazione: (2024)

Transfer Learning of Tabular Data by Finetuning Large Language Models
di: Rabbani, Shourav B., et al.
Pubblicazione: (2025)

Exploring and Benchmarking the Planning Capabilities of Large Language Models
di: Bohnet, Bernd, et al.
Pubblicazione: (2024)

Large Scale Transfer Learning for Tabular Data via Language Modeling
di: Gardner, Josh, et al.
Pubblicazione: (2024)

Binary Autoencoder for Mechanistic Interpretability of Large Language Models
di: Cho, Hakaze, et al.
Pubblicazione: (2025)

Exploring Multilingual Probing in Large Language Models: A Cross-Language Analysis
di: Li, Daoyang, et al.
Pubblicazione: (2024)

The Limited Impact of Medical Adaptation of Large Language and Vision-Language Models
di: Jeong, Daniel P., et al.
Pubblicazione: (2024)

Elephants Never Forget: Memorization and Learning of Tabular Data in Large Language Models
di: Bordt, Sebastian, et al.
Pubblicazione: (2024)

Labrador: Exploring the Limits of Masked Language Modeling for Laboratory Data
di: Bellamy, David R., et al.
Pubblicazione: (2023)

Large Language Models for Travel Behavior Prediction
di: Mo, Baichuan, et al.
Pubblicazione: (2023)

Should You Use Your Large Language Model to Explore or Exploit?
di: Harris, Keegan, et al.
Pubblicazione: (2025)

PoliTune: Analyzing the Impact of Data Selection and Fine-Tuning on Economic and Political Biases in Large Language Models
di: Agiza, Ahmed, et al.
Pubblicazione: (2024)

Language over Content: Tracing Cultural Understanding in Multilingual Large Language Models
di: Cho, Seungho, et al.
Pubblicazione: (2025)

Detecting Data Contamination from Reinforcement Learning Post-training for Large Language Models
di: Tao, Yongding, et al.
Pubblicazione: (2025)

An Overview of Large Language Models for Statisticians
di: Ji, Wenlong, et al.
Pubblicazione: (2025)

Exploring Anti-Aging Literature via ConvexTopics and Large Language Models
di: Yeganova, Lana E., et al.
Pubblicazione: (2026)

Beware of Calibration Data for Pruning Large Language Models
di: Ji, Yixin, et al.
Pubblicazione: (2024)

Diversity-oriented Data Augmentation with Large Language Models
di: Wang, Zaitian, et al.
Pubblicazione: (2025)

LLMSurgeon: Diagnosing Data Mixture of Large Language Models
di: Luo, Yaxin, et al.
Pubblicazione: (2026)

Aioli: A Unified Optimization Framework for Language Model Data Mixing
di: Chen, Mayee F., et al.
Pubblicazione: (2024)

Learning Mathematical Rules with Large Language Models
di: Gorceix, Antoine, et al.
Pubblicazione: (2024)

Active Preference Learning for Large Language Models
di: Muldrew, William, et al.
Pubblicazione: (2024)

Integration of Large Language Models and Federated Learning
di: Chen, Chaochao, et al.
Pubblicazione: (2023)

Test-Time Learning for Large Language Models
di: Hu, Jinwu, et al.
Pubblicazione: (2025)

Data Advisor: Dynamic Data Curation for Safety Alignment of Large Language Models
di: Wang, Fei, et al.
Pubblicazione: (2024)

From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies
di: Škrlj, Blaž, et al.
Pubblicazione: (2025)

Solving for X and Beyond: Can Large Language Models Solve Complex Math Problems with More-Than-Two Unknowns?
di: Kao, Kuei-Chun, et al.
Pubblicazione: (2024)

Federated Data-Efficient Instruction Tuning for Large Language Models
di: Qin, Zhen, et al.
Pubblicazione: (2024)

Rethinking Data Mixing from the Perspective of Large Language Models
di: Xu, Yuanjian, et al.
Pubblicazione: (2026)