:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Cavalin, Paulo, Sanctos, Cassia, Grave, Marcelo, Pinhanez, Claudio, Primerano, Yago
Format:	Preprint
Published:	2025
Subjects:	Computation and Language
Online Access:	https://arxiv.org/abs/2512.23711
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

The Non-Determinism of Small LLMs: Evidence of Low Answer Consistency in Repetition Trials of Standard Multiple-Choice Benchmarks
by: Pinhanez, Claudio, et al.
Published: (2025)

Improving Score Reliability of Multiple Choice Benchmarks with Consistency Evaluation and Altered Answer Choices
by: Cavalin, Paulo, et al.
Published: (2025)

Exploring Performance Variations in Finetuned Translators of Ultra-Low Resource Languages: Do Linguistic Differences Matter?
by: Gonçalves, Isabel, et al.
Published: (2025)

Sentence-level Aggregation of Lexical Metrics Correlates Stronger with Human Judgements than Corpus-level Aggregation
by: Cavalin, Paulo, et al.
Published: (2024)

Creating an African American-Sounding TTS: Guidelines, Technical Challenges,and Surprising Evaluations
by: Pinhanez, Claudio, et al.
Published: (2024)

Harnessing the Power of Artificial Intelligence to Vitalize Endangered Indigenous Languages: Technologies and Experiences
by: Pinhanez, Claudio, et al.
Published: (2024)

A methodological analysis of prompt perturbations and their effect on attack success rates
by: Machado, Tiago, et al.
Published: (2025)

LLMs as Agentic Cooperative Players in Multiplayer UNO
by: Matinez, Yago Romano, et al.
Published: (2025)

Are Economists Always More Introverted? Analyzing Consistency in Persona-Assigned LLMs
by: Reusens, Manon, et al.
Published: (2025)

Beyond Self-Consistency: Ensemble Reasoning Boosts Consistency and Accuracy of LLMs in Cancer Staging
by: Chang, Chia-Hsuan, et al.
Published: (2024)

Accuracy and Consistency of LLMs in the Registered Dietitian Exam: The Impact of Prompt Engineering and Knowledge Retrieval
by: Azimi, Iman, et al.
Published: (2024)

Contextual Metric Meta-Evaluation by Measuring Local Metric Accuracy
by: Deviyani, Athiya, et al.
Published: (2025)

Analyzing the Inherent Response Tendency of LLMs: Real-World Instructions-Driven Jailbreak
by: Du, Yanrui, et al.
Published: (2023)

To Know or Not To Know? Analyzing Self-Consistency of Large Language Models under Ambiguity
by: Sedova, Anastasiia, et al.
Published: (2024)

Analyzing FOMC Minutes: Accuracy and Constraints of Language Models
by: Kim, Wonseong, et al.
Published: (2023)

Meta-Evaluating Local LLMs: Rethinking Performance Metrics for Serious Games
by: Isaza-Giraldo, Andrés, et al.
Published: (2025)

Analyzing Reasoning Consistency in Large Multimodal Models under Cross-Modal Conflicts
by: Zhu, Zhihao, et al.
Published: (2026)

Worst-Case Input Generation for Concurrent Programs under Non-Monotone Resource Metrics
by: Pham, Long, et al.
Published: (2023)

Navigating the Metrics Maze: Reconciling Score Magnitudes and Accuracies
by: Kocmi, Tom, et al.
Published: (2024)

LogitScope: A Framework for Analyzing LLM Uncertainty Through Information Metrics
by: Ahmed, Farhan, et al.
Published: (2026)

AL-QASIDA: Analyzing LLM Quality and Accuracy Systematically in Dialectal Arabic
by: Robinson, Nathaniel R., et al.
Published: (2024)

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

Self-Training Meets Consistency: Improving LLMs' Reasoning with Consistency-Driven Rationale Evaluation
by: Lee, Jaehyeok, et al.
Published: (2024)

Revisiting Backdoor Attacks on LLMs: A Stealthy and Practical Poisoning Framework via Harmless Inputs
by: Kong, Jiawei, et al.
Published: (2025)

MetricalARGS: A Taxonomy for Studying Metrical Poetry with LLMs
by: Kranti, Chalamalasetti, et al.
Published: (2025)

Attention Consistency for LLMs Explanation
by: Lan, Tian, et al.
Published: (2025)

Analyzing Similarity Metrics for Data Selection for Language Model Pretraining
by: Sam, Dylan, et al.
Published: (2025)

Consistency Guided Knowledge Retrieval and Denoising in LLMs for Zero-shot Document-level Relation Triplet Extraction
by: Sun, Qi, et al.
Published: (2024)

Improving Factual Accuracy of Neural Table-to-Text Output by Addressing Input Problems in ToTTo
by: Sundararajan, Barkavi, et al.
Published: (2024)

LIFT: A Novel Framework for Enhancing Long-Context Understanding of LLMs via Long Input Fine-Tuning
by: Mao, Yansheng, et al.
Published: (2025)

Comparative Experimentation of Accuracy Metrics in Automated Medical Reporting: The Case of Otitis Consultations
by: Faber, Wouter, et al.
Published: (2023)

Too Consistent to Detect: A Study of Self-Consistent Errors in LLMs
by: Tan, Hexiang, et al.
Published: (2025)

Moneyball with LLMs: Analyzing Tabular Summarization in Sports Narratives
by: Upadhyay, Ritam, et al.
Published: (2025)

Tricking LLMs into Disobedience: Formalizing, Analyzing, and Detecting Jailbreaks
by: Rao, Abhinav, et al.
Published: (2023)

Analyzing Dialectical Biases in LLMs for Knowledge and Reasoning Benchmarks
by: Pan, Eileen, et al.
Published: (2025)

Can LLMs Recognize Toxicity? A Structured Investigation Framework and Toxicity Metric
by: Koh, Hyukhun, et al.
Published: (2024)

On the Sensitivity of Instruction-tuned LLMs to Harmful Sentences in Long Inputs
by: Ghorbanpour, Faeze, et al.
Published: (2025)

Leveraging Self-Attention for Input-Dependent Soft Prompting in LLMs
by: Muppidi, Ananth, et al.
Published: (2025)

The Order Effect: Investigating Prompt Sensitivity to Input Order in LLMs
by: Guan, Bryan, et al.
Published: (2025)

Do LLMs Provide Consistent Answers to Health-Related Questions across Languages?
by: Schlicht, Ipek Baris, et al.
Published: (2025)