Cover Image

Show, Don't Tell: Evaluating Large Language Models Beyond Textual Understanding with ChildPlay

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	de Carvalho, Gonçalo Hora, Knap, Oscar, Pollice, Robert
Format:	Preprint
Published:	2024
Subjects:	Artificial Intelligence Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Show, Don't Tell: Uncovering Implicit Character Portrayal using LLMs
by: Jaipersaud, Brandon, et al.
Published: (2024)

Tell, Don't Show!: Language Guidance Eases Transfer Across Domains in Images and Videos
by: Kalluri, Tarun, et al.
Published: (2024)

Language Models Don't Learn the Physical Manifestation of Language
by: Lee, Bruce W., et al.
Published: (2024)

Don't Change My View: Ideological Bias Auditing in Large Language Models
by: Kröger, Paul, et al.
Published: (2025)

Why Don't Prompt-Based Fairness Metrics Correlate?
by: Zayed, Abdelrahman, et al.
Published: (2024)

Don't Buy it! Reassessing the Ad Understanding Abilities of Contrastive Multimodal Models
by: Bavaresco, A., et al.
Published: (2024)

Don't Pass@k: A Bayesian Framework for Large Language Model Evaluation
by: Hariri, Mohsen, et al.
Published: (2025)

Large Language Models Must Be Taught to Know What They Don't Know
by: Kapoor, Sanyam, et al.
Published: (2024)

Don't Pay Attention
by: Hammoud, Mohammad, et al.
Published: (2025)

Do Retrieval Augmented Language Models Know When They Don't Know?
by: Zhou, Youchao, et al.
Published: (2025)

C-Causal Blindness
by: de Carvalho, Gonçalo Hora
Published: (2022)

Reasoning Models Reason Well, Until They Don't
by: Rameshkumar, Revanth, et al.
Published: (2025)

Tell, Don't Show: Leveraging Language Models' Abstractive Retellings to Model Literary Themes
by: Lucy, Li, et al.
Published: (2025)

Role-Playing Evaluation for Large Language Models
by: Boudouri, Yassine El, et al.
Published: (2025)

Don't Take Things Out of Context: Attention Intervention for Enhancing Chain-of-Thought Reasoning in Large Language Models
by: Yan, Shaotian, et al.
Published: (2025)

Don't Believe Everything You Read: Enhancing Summarization Interpretability through Automatic Identification of Hallucinations in Large Language Models
by: Vakharia, Priyesh, et al.
Published: (2023)

The Accuracy Paradox in RLHF: When Better Reward Models Don't Yield Better Language Models
by: Chen, Yanjun, et al.
Published: (2024)

Too Nice to Tell the Truth: Quantifying Agreeableness-Driven Sycophancy in Role-Playing Language Models
by: Shah, Arya, et al.
Published: (2026)

Don't Forget Your Reward Values: Language Model Alignment via Value-based Calibration
by: Mao, Xin, et al.
Published: (2024)

Don't Let It Fade: Preserving Edits in Diffusion Language Models via Token Timestep Allocation
by: Kim, Woojin, et al.
Published: (2025)

RPGBENCH: Evaluating Large Language Models as Role-Playing Game Engines
by: Yu, Pengfei, et al.
Published: (2025)

Reasoning Models Don't Always Say What They Think
by: Chen, Yanda, et al.
Published: (2025)

Can AI Assistants Know What They Don't Know?
by: Cheng, Qinyuan, et al.
Published: (2024)

Empowering Large Language Models for Textual Data Augmentation
by: Li, Yichuan, et al.
Published: (2024)

Honest AI: Fine-Tuning "Small" Language Models to Say "I Don't Know", and Reducing Hallucination in RAG
by: Chen, Xinxi, et al.
Published: (2024)

Reasoning about Uncertainty: Do Reasoning Models Know When They Don't Know?
by: Mei, Zhiting, et al.
Published: (2025)

Textual Aesthetics in Large Language Models
by: Jiang, Lingjie, et al.
Published: (2024)

Evaluating Spatial Understanding of Large Language Models
by: Yamada, Yutaro, et al.
Published: (2023)

Meta-Judging with Large Language Models: Concepts, Methods, and Challenges
by: Silva, Hugo, et al.
Published: (2026)

AI-driven control of bioelectric signalling for real-time topological reorganization of cells
by: de Carvalho, Gonçalo Hora
Published: (2025)

Don't Think Twice! Over-Reasoning Impairs Confidence Calibration
by: Lacombe, Romain, et al.
Published: (2025)

sDPO: Don't Use Your Data All at Once
by: Kim, Dahyun, et al.
Published: (2024)

Larger Language Models Don't Care How You Think: Why Chain-of-Thought Prompting Fails in Subjective Tasks
by: Chochlakis, Georgios, et al.
Published: (2024)

Don't Think of the White Bear: Ironic Negation in Transformer Models Under Cognitive Load
by: Mann, Logan, et al.
Published: (2025)

To Tell The Truth: Language of Deception and Language Models
by: Hazra, Sanchaita, et al.
Published: (2023)

LLM Cyber Evaluations Don't Capture Real-World Risk
by: Lukošiūtė, Kamilė, et al.
Published: (2025)

Gradients with Respect to Semantics Preserving Embeddings Tell the Uncertainty of Large Language Models
by: Li, Mingda, et al.
Published: (2026)

Don't Overthink it. Preferring Shorter Thinking Chains for Improved LLM Reasoning
by: Hassid, Michael, et al.
Published: (2025)

Enhancing Traffic Prediction with Textual Data Using Large Language Models
by: Huang, Xiannan
Published: (2024)

Beyond Facts: Evaluating Intent Hallucination in Large Language Models
by: Hao, Yijie, et al.
Published: (2025)