Buchumschlag

Uniform Discretized Integrated Gradients: An effective attribution based method for explaining large language models

Fuente: arXiv

Gespeichert in:

Bibliographische Detailangaben
Hauptverfasser:	Roy, Swarnava Sinha, Kundu, Ayan
Format:	Preprint
Veröffentlicht:	2024
Schlagworte:	Computation and Language Artificial Intelligence
Online-Zugang:	Acceder al recurso
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Ähnliche Einträge

On the attribution of confidence to large language models
von: Keeling, Geoff, et al.
Veröffentlicht: (2024)

Can adversarial attacks by large language models be attributed?
von: Cebrian, Manuel, et al.
Veröffentlicht: (2024)

Dissociating language and thought in large language models
von: Mahowald, Kyle, et al.
Veröffentlicht: (2023)

Emergent effects of scaling on the functional hierarchies within large language models
von: Bogdan, Paul C.
Veröffentlicht: (2025)

Streamlining evidence based clinical recommendations with large language models
von: Li, Dubai, et al.
Veröffentlicht: (2025)

Multi-round jailbreak attack on large language models
von: Zhou, Yihua, et al.
Veröffentlicht: (2024)

The 20 questions game to distinguish large language models
von: Richardeau, Gurvan, et al.
Veröffentlicht: (2024)

Quantifying non deterministic drift in large language models
von: Nicholson, Claire
Veröffentlicht: (2026)

Can large language models build causal graphs?
von: Long, Stephanie, et al.
Veröffentlicht: (2023)

Response: Emergent analogical reasoning in large language models
von: Hodel, Damian, et al.
Veröffentlicht: (2023)

Representation in large language models
von: Yetman, Cameron
Veröffentlicht: (2025)

Failure of contextual invariance in large language models
von: Kumar, Sagar, et al.
Veröffentlicht: (2026)

A survey of textual cyber abuse detection using cutting-edge language models and large language models
von: Diaz-Garcia, Jose A., et al.
Veröffentlicht: (2025)

Strong and weak alignment of large language models with human values
von: Khamassi, Mehdi, et al.
Veröffentlicht: (2024)

Correcting misinformation on social media with a large language model
von: Zhou, Xinyi, et al.
Veröffentlicht: (2024)

A review on the use of large language models as virtual tutors
von: García-Méndez, Silvia, et al.
Veröffentlicht: (2024)

Evaluating large language models in medical applications: a survey
von: Chen, Xiaolan, et al.
Veröffentlicht: (2024)

MathDivide: Improved mathematical reasoning by large language models
von: Srivastava, Saksham Sahai, et al.
Veröffentlicht: (2024)

Re-evaluating Theory of Mind evaluation in large language models
von: Hu, Jennifer, et al.
Veröffentlicht: (2025)

Disentangling generalization and memorization in large language models using chess
von: Pleiss, Leonard S., et al.
Veröffentlicht: (2026)

AI-AI Bias: large language models favor communications generated by large language models
von: Laurito, Walter, et al.
Veröffentlicht: (2024)

Alignment faking in large language models
von: Greenblatt, Ryan, et al.
Veröffentlicht: (2024)

Optimizing watermarks for large language models
von: Wouters, Bram
Veröffentlicht: (2023)

Uncovering inequalities in new knowledge learning by large language models across different languages
von: Wang, Chenglong, et al.
Veröffentlicht: (2025)

Entry-level guide to the use of large language models for medical research
von: Jin, Qiao, et al.
Veröffentlicht: (2024)

Facilitating large language model Russian adaptation with Learned Embedding Propagation
von: Tikhomirov, Mikhail, et al.
Veröffentlicht: (2024)

MacBehaviour: An R package for behavioural experimentation on large language models
von: Duan, Xufeng, et al.
Veröffentlicht: (2024)

Hyacinth6B: A large language model for Traditional Chinese
von: Song, Chih-Wei, et al.
Veröffentlicht: (2024)

Can large language models understand uncommon meanings of common words?
von: Wu, Jinyang, et al.
Veröffentlicht: (2024)

Generating bilingual example sentences with large language models as lexicography assistants
von: Merx, Raphael, et al.
Veröffentlicht: (2024)

Leveraging large language models for efficient representation learning for entity resolution
von: Xu, Xiaowei, et al.
Veröffentlicht: (2024)

Are they human? Detecting large language models by probing human memory constraints
von: Schug, Simon, et al.
Veröffentlicht: (2026)

A blind spot for large language models: Supradiegetic linguistic information
von: Zimmerman, Julia Witte, et al.
Veröffentlicht: (2023)

ARC-Encoder: learning compressed text representations for large language models
von: Pilchen, Hippolyte, et al.
Veröffentlicht: (2025)

Enhancing reasoning accuracy in large language models during inference time
von: Sharma, Vinay, et al.
Veröffentlicht: (2026)

ZNO-Eval: Benchmarking reasoning capabilities of large language models in Ukrainian
von: Syromiatnikov, Mykyta, et al.
Veröffentlicht: (2025)

ChildEval: When large language models meet children's personalities
von: Luo, Yanyan, et al.
Veröffentlicht: (2026)

Medical large language models are easily distracted
von: Vishwanath, Krithik, et al.
Veröffentlicht: (2025)

What can large language models do for sustainable food?
von: Thomas, Anna T., et al.
Veröffentlicht: (2025)

Long-form factuality in large language models
von: Wei, Jerry, et al.
Veröffentlicht: (2024)