Imagen de Portada

Evolutionary Search for Automated Design of Uncertainty Quantification Methods

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Seleznyov, Mikhail, Korbut, Daniil, Moskvoretskii, Viktor, Somov, Oleg, Panchenko, Alexander, Tutubalina, Elena
Formato:	Preprint
Publicado:	2026
Materias:	Computation and Language Artificial Intelligence
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

When Punctuation Matters: A Large-Scale Comparison of Prompt Robustness Methods for LLMs
por: Seleznyov, Mikhail, et al.
Publicado: (2025)

Breaking the Chain: A Causal Analysis of LLM Faithfulness to Intermediate Structures
por: Somov, Oleg, et al.
Publicado: (2026)

Leveraging LLM Parametric Knowledge for Fact Checking without Retrieval
por: Vazhentsev, Artem, et al.
Publicado: (2026)

Confidence Estimation for Error Detection in Text-to-SQL Systems
por: Somov, Oleg, et al.
Publicado: (2025)

The benefits of query-based KGQA systems for complex and temporal questions in LLM era
por: Alekseev, Artem, et al.
Publicado: (2025)

<think> So let's replace this phrase with insult... </think> Lessons learned from generation of toxic texts with LLMs
por: Pletenev, Sergey, et al.
Publicado: (2025)

Harnessing non-adversarial robustness in large language models
por: Zhou, Qinghua, et al.
Publicado: (2026)

The Chronicles of RiDiC: Generating Datasets with Controlled Popularity Distribution for Long-form Factuality Evaluation
por: Braslavski, Pavel, et al.
Publicado: (2026)

xCOMET-lite: Bridging the Gap Between Efficiency and Quality in Learned MT Evaluation Metrics
por: Larionov, Daniil, et al.
Publicado: (2024)

SynthDetoxM: Modern LLMs are Few-Shot Parallel Detoxification Data Annotators
por: Moskovskiy, Daniil, et al.
Publicado: (2025)

Tracing Persona Vectors Through LLM Pretraining
por: Moskvoretskii, Viktor, et al.
Publicado: (2026)

Fact-Checking the Output of Large Language Models via Token-Level Uncertainty Quantification
por: Fadeeva, Ekaterina, et al.
Publicado: (2024)

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

Evaluating Uncertainty Quantification Methods in Argumentative Large Language Models
por: Zhou, Kevin, et al.
Publicado: (2025)

SparseGrad: A Selective Method for Efficient Fine-tuning of MLP Layers
por: Chekalina, Viktoriia, et al.
Publicado: (2024)

MultiParaDetox: Extending Text Detoxification with Parallel Data to New Languages
por: Dementieva, Daryna, et al.
Publicado: (2024)

S3: A Simple Strong Sample-effective Multimodal Dialog System
por: Rykov, Elisei, et al.
Publicado: (2024)

TaxoLLaMA: WordNet-based Model for Solving Multiple Lexical Semantic Tasks
por: Moskvoretskii, Viktor, et al.
Publicado: (2024)

Agentic Uncertainty Quantification
por: Zhang, Jiaxin, et al.
Publicado: (2026)

RuCCoD: Towards Automated ICD Coding in Russian
por: Nesterov, Aleksandr, et al.
Publicado: (2025)

Anatomy of Unlearning: The Dual Impact of Fact Salience and Model Fine-Tuning
por: Borisiuk, Anna, et al.
Publicado: (2026)

Emergent Misalignment via In-Context Learning: Narrow in-context examples can produce broadly misaligned LLMs
por: Afonin, Nikita, et al.
Publicado: (2025)

Combining Confidence Elicitation and Sample-based Methods for Uncertainty Quantification in Misinformation Mitigation
por: Rivera, Mauricio, et al.
Publicado: (2024)

MAQA: Evaluating Uncertainty Quantification in LLMs Regarding Data Uncertainty
por: Yang, Yongjin, et al.
Publicado: (2024)

BALI: Enhancing Biomedical Language Representations through Knowledge Graph and Language Model Alignment
por: Sakhovskiy, Andrey, et al.
Publicado: (2025)

CSS: Contrastive Semantic Similarity for Uncertainty Quantification of LLMs
por: Ao, Shuang, et al.
Publicado: (2024)

Adaptive Retrieval Without Self-Knowledge? Bringing Uncertainty Back Home
por: Moskvoretskii, Viktor, et al.
Publicado: (2025)

SPUQ: Perturbation-Based Uncertainty Quantification for Large Language Models
por: Gao, Xiang, et al.
Publicado: (2024)

Uncertainty-Based Methods for Automated Process Reward Data Construction and Output Aggregation in Mathematical Reasoning
por: Han, Jiuzhou, et al.
Publicado: (2025)

Semantic Consistency-Based Uncertainty Quantification for Factuality in Radiology Report Generation
por: Wang, Chenyu, et al.
Publicado: (2024)

Uncertainty Quantification of Large Language Models through Multi-Dimensional Responses
por: Chen, Tiejin, et al.
Publicado: (2025)

Uncertainty Quantification in Large Language Models Through Convex Hull Analysis
por: Catak, Ferhat Ozgur, et al.
Publicado: (2024)

Do I look like a `cat.n.01` to you? A Taxonomy Image Generation Benchmark
por: Moskvoretskii, Viktor, et al.
Publicado: (2025)

SmurfCat at SemEval-2024 Task 6: Leveraging Synthetic Data for Hallucination Detection
por: Rykov, Elisei, et al.
Publicado: (2024)

Kernel Language Entropy: Fine-grained Uncertainty Quantification for LLMs from Semantic Similarities
por: Nikitin, Alexander, et al.
Publicado: (2024)

Mind the Ambiguity: Aleatoric Uncertainty Quantification in LLMs for Safe Medical Question Answering
por: Liu, Yaokun, et al.
Publicado: (2026)

SIMBA UQ: Similarity-Based Aggregation for Uncertainty Quantification in Large Language Models
por: Bhattacharjya, Debarun, et al.
Publicado: (2025)

Optimizing Instruction Synthesis: Effective Exploration of Evolutionary Space with Tree Search
por: Li, Chenglin, et al.
Publicado: (2024)

Search Wisely: Mitigating Sub-optimal Agentic Searches By Reducing Uncertainty
por: Wu, Peilin, et al.
Publicado: (2025)

Calibrating Uncertainty Quantification of Multi-Modal LLMs using Grounding
por: Padhi, Trilok, et al.
Publicado: (2025)