Cover Image

Actions Speak Louder than Prompts: A Large-Scale Study of LLMs for Graph Inference

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Finkelshtein, Ben, Cucerzan, Silviu, Jauhar, Sujay Kumar, White, Ryen
Format:	Preprint
Published:	2025
Subjects:	Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Idea2Plan: Exploring AI-Powered Research Planning
by: Huang, Jin, et al.
Published: (2025)

Neon: News Entity-Interaction Extraction for Enhanced Question Answering
by: Singhania, Sneha, et al.
Published: (2024)

ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models
by: Baek, Jinheon, et al.
Published: (2024)

Knowledge-Augmented Large Language Models for Personalized Contextual Query Suggestion
by: Baek, Jinheon, et al.
Published: (2023)

Evaluating Style-Personalized Text Generation: Challenges and Directions
by: Jangra, Anubhav, et al.
Published: (2025)

Knowledge-Centric Templatic Views of Documents
by: Cachola, Isabel, et al.
Published: (2024)

Choices Speak Louder than Questions
by: Cho, Gyeongje, et al.
Published: (2025)

Actions Speak Louder than Words: Agent Decisions Reveal Implicit Biases in Language Models
by: Li, Yuxuan, et al.
Published: (2025)

Do Images Speak Louder than Words? Investigating the Effect of Textual Misinformation in VLMs
by: Zhang, Chi, et al.
Published: (2026)

Conversational User-AI Intervention: A Study on Prompt Rewriting for Improved LLM Response Generation
by: Sarkar, Rupak, et al.
Published: (2025)

TnT-LLM: Text Mining at Scale with Large Language Models
by: Wan, Mengting, et al.
Published: (2024)

Captions Speak Louder than Images: Generalizing Foundation Models for E-commerce from High-quality Multimodal Instruction Data
by: Ling, Xinyi, et al.
Published: (2024)

Images Speak Louder than Words: Understanding and Mitigating Bias in Vision-Language Model from a Causal Mediation Perspective
by: Weng, Zhaotian, et al.
Published: (2024)

Beyond Output Critique: Self-Correction via Task Distillation
by: Rahmani, Hossein A., et al.
Published: (2026)

Group Preference Alignment: Customized LLM Response Generation from In-Situ Conversations
by: Mondal, Ishani, et al.
Published: (2025)

Revisiting Direct Speech-to-Text Translation with Speech LLMs: Better Scaling than CoT Prompting?
by: Pareras, Oriol, et al.
Published: (2025)

HiSpec: Hierarchical Speculative Decoding for LLMs
by: Kumar, Avinash, et al.
Published: (2025)

Disentangled Concepts Speak Louder Than Words: Explainable Video Action Recognition
by: Lee, Jongseo, et al.
Published: (2025)

Actions Speak Louder Than Chats: Investigating AI Chatbot Age Gating
by: Figueira, Olivia, et al.
Published: (2026)

Actions Speak Louder than Words: Trillion-Parameter Sequential Transducers for Generative Recommendations
by: Zhai, Jiaqi, et al.
Published: (2024)

Investigating Implicit Bias in Large Language Models: A Large-Scale Study of Over 50 LLMs
by: Kumar, Divyanshu, et al.
Published: (2024)

WildFeedback: Aligning LLMs With In-situ User Interactions And Feedback
by: Shi, Taiwei, et al.
Published: (2024)

Making Large Language Models Speak Tulu: Structured Prompting for an Extremely Low-Resource Language
by: Devadiga, Prathamesh, et al.
Published: (2026)

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

Text Speaks Louder than Vision: ASCII Art Reveals Textual Biases in Vision-Language Models
by: Wang, Zhaochen, et al.
Published: (2025)

ART: Adaptive Response Tuning Framework -- A Multi-Agent Tournament-Based Approach to LLM Response Optimization
by: Khan, Omer Jauhar
Published: (2025)

Thinking Ahead: Prospection-Guided Retrieval of Memory with Language Models
by: Chopra, Harshita, et al.
Published: (2026)

Skeletons Speak Louder than Text: A Motion-Aware Pretraining Paradigm for Video-Based Person Re-Identification
by: Lin, Rifen, et al.
Published: (2025)

Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering
by: Cheng, Zifeng, et al.
Published: (2025)

PrExMe! Large Scale Prompt Exploration of Open Source LLMs for Machine Translation and Summarization Evaluation
by: Leiter, Christoph, et al.
Published: (2024)

BayesPrompt: Prompting Large-Scale Pre-Trained Language Models on Few-shot Inference via Debiased Domain Abstraction
by: Li, Jiangmeng, et al.
Published: (2024)

Do Actions Speak Louder than Words? Sustainability Signals and Claims to Attract Business Angel Financing
by: Julian Bafera, et al.
Published: (2026)

S2LPP: Small-to-Large Prompt Prediction across LLMs
by: Cheng, Liang, et al.
Published: (2025)

Test-Time Speculation
by: Kumar, Avinash, et al.
Published: (2026)

Triggering Hallucinations in LLMs: A Quantitative Study of Prompt-Induced Hallucination in Large Language Models
by: Sato, Makoto
Published: (2025)

Let Me Speak Freely? A Study on the Impact of Format Restrictions on Performance of Large Language Models
by: Tam, Zhi Rui, et al.
Published: (2024)

Evaluating the Effectiveness of Black-Box Prompt Optimization as the Scale of LLMs Continues to Grow
by: Zhou, Ziyu, et al.
Published: (2025)

Mind the Gap: Evaluating Model- and Agentic-Level Vulnerabilities in LLMs with Action Graphs
by: Wicaksono, Ilham, et al.
Published: (2025)

Summarize Before You Speak with ARACH: A Training-Free Inference-Time Plug-In for Enhancing LLMs via Global Attention Reallocation
by: Wang, Jingtao, et al.
Published: (2026)

Machine Translation with Large Language Models: Decoder Only vs. Encoder-Decoder
by: M., Abhinav P., et al.
Published: (2024)