Cover Image

Personalized Help for Optimizing Low-Skilled Users' Strategy

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Gu, Feng, Wongkamjan, Wichayaporn, Kummerfeld, Jonathan K., Peskoff, Denis, May, Jonathan, Boyd-Graber, Jordan
Format:	Preprint
Published:	2024
Subjects:	Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Should I Trust You? Detecting Deception in Negotiations using Counterfactual RL
by: Wongkamjan, Wichayaporn, et al.
Published: (2025)

More Victories, Less Cooperation: Assessing Cicero's Diplomacy Play
by: Wongkamjan, Wichayaporn, et al.
Published: (2024)

What if Red Can Talk? Dynamic Dialogue Generation Using Large Language Models
by: Nananukul, Navapat, et al.
Published: (2024)

Whose Boat Does it Float? Improving Personalization in Preference Tuning via Inferred User Personas
by: Balepur, Nishant, et al.
Published: (2025)

DiscoTrace: Representing and Comparing Answering Strategies of Humans and LLMs in Information-Seeking Question Answering
by: Srikanth, Neha, et al.
Published: (2026)

A Good Plan is Hard to Find: Aligning Models with Preferences is Misaligned with What Helps Users
by: Balepur, Nishant, et al.
Published: (2025)

KARL: Knowledge-Aware Retrieval and Representations aid Retention and Learning in Students
by: Shu, Matthew, et al.
Published: (2024)

Reverse Question Answering: Can an LLM Write a Question so Hard (or Bad) that it Can't Answer?
by: Balepur, Nishant, et al.
Published: (2024)

Large Language Models Help Humans Verify Truthfulness -- Except When They Are Convincingly Wrong
by: Si, Chenglei, et al.
Published: (2023)

Which of These Best Describes Multiple Choice Evaluation with LLMs? A) Forced B) Flawed C) Fixable D) All of the Above
by: Balepur, Nishant, et al.
Published: (2025)

The Rise of AI-Generated Content in Wikipedia
by: Brooks, Creston, et al.
Published: (2024)

How the Advent of Ubiquitous Large Language Models both Stymie and Turbocharge Dynamic Adversarial Question Generation
by: Sung, Yoo Yeon, et al.
Published: (2024)

AUDITA: A New Dataset to Audit Humans vs. AI Skill at Audio QA
by: Kabir, Tasnim, et al.
Published: (2026)

Simple and Effective Baselines for Code Summarisation Evaluation
by: Robinson, Jade, et al.
Published: (2025)

Labeled Interactive Topic Models
by: Seelman, Kyle, et al.
Published: (2023)

Large Language Models Struggle to Describe the Haystack without Human Help: Human-in-the-loop Evaluation of Topic Models
by: Li, Zongxia, et al.
Published: (2025)

Language Models Don't Know What You Want: Evaluating Personalization in Deep Research Needs Real Users
by: Balepur, Nishant, et al.
Published: (2026)

ProxAnn: Use-Oriented Evaluations of Topic Models and Document Clustering
by: Hoyle, Alexander, et al.
Published: (2025)

NAVIG: Natural Language-guided Analysis with Vision Language Models for Image Geo-localization
by: Zhang, Zheyuan, et al.
Published: (2025)

Style Transfer with Multi-iteration Preference Optimization
by: Liu, Shuai, et al.
Published: (2024)

Your Students Don't Use LLMs Like You Wish They Did
by: Kobler, Sebastian, et al.
Published: (2026)

Large Language Models Are Effective Human Annotation Assistants, But Not Good Independent Annotators
by: Gu, Feng, et al.
Published: (2025)

Aligning AI Research with the Needs of Clinical Coding Workflows: Eight Recommendations Based on US Data Analysis and Critical Review
by: Gan, Yidong, et al.
Published: (2024)

CFMatch: Aligning Automated Answer Equivalence Evaluation with Expert Judgments For Open-Domain Question Answering
by: Li, Zongxia, et al.
Published: (2024)

Authorship Style Transfer with Policy Optimization
by: Liu, Shuai, et al.
Published: (2024)

SQLucid: Grounding Natural Language Database Queries with Interactive Explanations
by: Tian, Yuan, et al.
Published: (2024)

Do great minds think alike? Investigating Human-AI Complementarity in Question Answering with CAIMIRA
by: Gor, Maharshi, et al.
Published: (2024)

SciDoc2Diagrammer-MAF: Towards Generation of Scientific Diagrams from Documents guided by Multi-Aspect Feedback Refinement
by: Mondal, Ishani, et al.
Published: (2024)

Is your benchmark truly adversarial? AdvScore: Evaluating Human-Grounded Adversarialness
by: Sung, Yoo Yeon, et al.
Published: (2024)

GRACE: A Granular Benchmark for Evaluating Model Calibration against Human Calibration
by: Sung, Yoo Yeon, et al.
Published: (2025)

A SMART Mnemonic Sounds like "Glue Tonic": Mixing LLMs with Student Feedback to Make Mnemonic Learning Stick
by: Balepur, Nishant, et al.
Published: (2024)

PEDANTS: Cheap but Effective and Interpretable Answer Equivalence
by: Li, Zongxia, et al.
Published: (2024)

SMART-Editor: A Multi-Agent Framework for Human-Like Design Editing with Structural Integrity
by: Mondal, Ishani, et al.
Published: (2025)

An Empirical Analysis of Static Analysis Methods for Detection and Mitigation of Code Library Hallucinations
by: Miranda-Pena, Clarissa, et al.
Published: (2026)

Do Text-to-Vis Benchmarks Test Real Use of Visualisations?
by: Nguyen, Hy, et al.
Published: (2024)

Conceptual Steganography
by: Zhou, Zhejian, et al.
Published: (2026)

CANVAS: Continuity-Aware Narratives via Visual Agentic Storyboarding
by: Mondal, Ishani, et al.
Published: (2026)

DRACULA: Hunting for the Actions Users Want Deep Research Agents to Execute
by: Balepur, Nishant, et al.
Published: (2026)

A Mechanistic Understanding of Alignment Algorithms: A Case Study on DPO and Toxicity
by: Lee, Andrew, et al.
Published: (2024)

Pregnant Questions: The Importance of Pragmatic Awareness in Maternal Health Question Answering
by: Srikanth, Neha, et al.
Published: (2023)