Cover Image

DyKnow: Dynamically Verifying Time-Sensitive Factual Knowledge in LLMs

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Mousavi, Seyed Mahed, Alghisi, Simone, Riccardi, Giuseppe
Format:	Preprint
Published:	2024
Subjects:	Computation and Language Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

V-DyKnow: A Dynamic Benchmark for Time-Sensitive Knowledge in Vision Language Models
by: Mousavi, Seyed Mahed, et al.
Published: (2026)

LLMs as Repositories of Factual Knowledge: Limitations and Solutions
by: Mousavi, Seyed Mahed, et al.
Published: (2025)

What Does Loss Optimization Actually Teach, If Anything? Knowledge Dynamics in Continual Pre-training of LLMs
by: Mousavi, Seyed Mahed, et al.
Published: (2026)

Should We Fine-Tune or RAG? Evaluating Different Techniques to Adapt LLMs for Dialogue
by: Alghisi, Simone, et al.
Published: (2024)

Are LLMs Robust for Spoken Dialogues?
by: Mousavi, Seyed Mahed, et al.
Published: (2024)

[De|Re]constructing VLMs' Reasoning in Counting
by: Alghisi, Simone, et al.
Published: (2025)

CIVET: Systematic Evaluation of Understanding in VLMs
by: Rizzoli, Massimo, et al.
Published: (2025)

Getting to the Point: Pointing Improves LVLMs at Counting
by: Alghisi, Simone, et al.
Published: (2026)

Garbage In, Reasoning Out? Why Benchmark Scores are Unreliable and What to Do About It
by: Mousavi, Seyed Mahed, et al.
Published: (2025)

Can LLMs Refuse Questions They Do Not Know? Measuring Knowledge-Aware Refusal in Factual Tasks
by: Pan, Wenbo, et al.
Published: (2025)

Improving Factuality in LLMs via Inference-Time Knowledge Graph Construction
by: Wu, Shanglin, et al.
Published: (2025)

Will LLMs Replace the Encoder-Only Models in Temporal Relation Classification?
by: Roccabruna, Gabriel, et al.
Published: (2024)

KnowHalu: Hallucination Detection via Multi-Form Knowledge Based Factual Checking
by: Zhang, Jiawei, et al.
Published: (2024)

KnowRL: Exploring Knowledgeable Reinforcement Learning for Factuality
by: Ren, Baochang, et al.
Published: (2025)

Time Sensitive Knowledge Editing through Efficient Finetuning
by: Ge, Xiou, et al.
Published: (2024)

MedReason: Eliciting Factual Medical Reasoning Steps in LLMs via Knowledge Graphs
by: Wu, Juncheng, et al.
Published: (2025)

LLMs Are Not Intelligent Thinkers: Introducing Mathematical Topic Tree Benchmark for Comprehensive Evaluation of LLMs
by: Davoodi, Arash Gholami, et al.
Published: (2024)

Towards a Holistic Evaluation of LLMs on Factual Knowledge Recall
by: Yuan, Jiaqing, et al.
Published: (2024)

FACTORY: A Challenging Human-Verified Prompt Set for Long-Form Factuality
by: Chen, Mingda, et al.
Published: (2025)

KG-FPQ: Evaluating Factuality Hallucination in LLMs with Knowledge Graph-based False Premise Questions
by: Zhu, Yanxu, et al.
Published: (2024)

Global-Liar: Factuality of LLMs over Time and Geographic Regions
by: Mirza, Shujaat, et al.
Published: (2024)

Is Factuality Enhancement a Free Lunch For LLMs? Better Factuality Can Lead to Worse Context-Faithfulness
by: Bi, Baolong, et al.
Published: (2024)

Knowledgeable In-Context Tuning: Exploring and Exploiting Factual Knowledge for In-Context Learning
by: Wang, Jianing, et al.
Published: (2023)

GenKnowSub: Improving Modularity and Reusability of LLMs through General Knowledge Subtraction
by: Bagherifard, Mohammadtaha, et al.
Published: (2025)

Aligning Knowledge Graphs and Language Models for Factual Accuracy
by: Nishat, Nur A Zarin, et al.
Published: (2025)

CounterRefine: Answer-Conditioned Counterevidence Retrieval for Inference-Time Knowledge Repair in Factual Question Answering
by: Huang, Tianyi, et al.
Published: (2026)

Reasoning Factual Knowledge in Structured Data with Large Language Models
by: Huang, Sirui, et al.
Published: (2024)

Self-Alignment for Factuality: Mitigating Hallucinations in LLMs via Self-Evaluation
by: Zhang, Xiaoying, et al.
Published: (2024)

Editing Factual Knowledge and Explanatory Ability of Medical Large Language Models
by: Xu, Derong, et al.
Published: (2024)

Cracking Factual Knowledge: A Comprehensive Analysis of Degenerate Knowledge Neurons in Large Language Models
by: Chen, Yuheng, et al.
Published: (2024)

CompassVerifier: A Unified and Robust Verifier for LLMs Evaluation and Outcome Reward
by: Liu, Shudong, et al.
Published: (2025)

What Models Know, How Well They Know It: Knowledge-Weighted Fine-Tuning for Learning When to Say "I Don't Know"
by: Lee, Joosung, et al.
Published: (2026)

Knowing What LLMs DO NOT Know: A Simple Yet Effective Self-Detection Method
by: Zhao, Yukun, et al.
Published: (2023)

LLM Factoscope: Uncovering LLMs' Factual Discernment through Inner States Analysis
by: He, Jinwen, et al.
Published: (2023)

Are the Hidden States Hiding Something? Testing the Limits of Factuality-Encoding Capabilities in LLMs
by: Servedio, Giovanni, et al.
Published: (2025)

Mitigating Geospatial Knowledge Hallucination in Large Language Models: Benchmarking and Dynamic Factuality Aligning
by: Wang, Shengyuan, et al.
Published: (2025)

Unveiling Factual Recall Behaviors of Large Language Models through Knowledge Neurons
by: Wang, Yifei, et al.
Published: (2024)

Do Large Language Models Know Conflict? Investigating Parametric vs. Non-Parametric Knowledge of LLMs for Conflict Forecasting
by: Nemkova, Apollinaire Poli, et al.
Published: (2025)

Know More, Know Clearer: A Meta-Cognitive Framework for Knowledge Augmentation in Large Language Models
by: Chen, Hao, et al.
Published: (2026)

Collective Reasoning Among LLMs: A Framework for Answer Validation Without Ground Truth
by: Davoudi, Seyed Pouyan Mousavi, et al.
Published: (2025)