Image de couverture de livre

Evaluating Evidence Grounding Under User Pressure in Instruction-Tuned Language Models

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Koneru, Sai, Joe, Elphin, Kirchhoff, Christine, Wu, Jian, Rajtmajer, Sarah
Format:	Preprint
Publié:	2026
Sujets:	Computation and Language
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Assessing the Effectiveness of GPT-4o in Climate Change Evidence Synthesis and Systematic Assessments: Preliminary Insights
par: Joe, Elphin Tom, et autres
Publié: (2024)

Can Large Language Models Discern Evidence for Scientific Hypotheses? Case Studies in the Social Sciences
par: Koneru, Sai, et autres
Publié: (2023)

Context Selection for Hypothesis and Statistical Evidence Extraction from Full-Text Scientific Articles
par: Koneru, Sai, et autres
Publié: (2026)

Many Ways to Be Fake: Benchmarking Fake News Detection Under Strategy-Driven AI Generation
par: Wang, Xinyu, et autres
Publié: (2026)

The Unappreciated Role of Intent in Algorithmic Moderation of Social Media Content
par: Wang, Xinyu, et autres
Publié: (2024)

What Are Research Hypotheses?
par: Wu, Jian, et autres
Publié: (2025)

Perspectives from India: Opportunities and Challenges for AI Replication Prediction to Improve Confidence in Published Research
par: Chakravorti, Tatiana, et autres
Publié: (2023)

Reproducibility, Replicability, and Transparency in Research: What 430 Professors Think in Universities across the USA and India
par: Chakravorti, Tatiana, et autres
Publié: (2024)

Have LLMs Reopened the Pandora's Box of AI-Generated Fake News?
par: Wang, Xinyu, et autres
Publié: (2024)

Monolingual and Multilingual Misinformation Detection for Low-Resource Languages: A Comprehensive Survey
par: Wang, Xinyu, et autres
Publié: (2024)

The Failed Migration of Academic Twitter: A Case Study of Precocious Adopters
par: Wang, Xinyu, et autres
Publié: (2024)

CC30k: A Citation Contexts Dataset for Reproducibility-Oriented Sentiment Analysis
par: Obadage, Rochana R., et autres
Publié: (2025)

Contextual Refinement of Translations: Large Language Models for Sentence and Document-Level Post-Editing
par: Koneru, Sai, et autres
Publié: (2023)

OmniFusion: Simultaneous Multilingual Multimodal Translations via Modular Fusion
par: Koneru, Sai, et autres
Publié: (2025)

UPDESH: Synthesizing Grounded Instruction Tuning Data for 13 Indic Languages
par: Chitale, Pranjal A., et autres
Publié: (2025)

Efficient Tuning of Large Language Models for Knowledge-Grounded Dialogue Generation
par: Zhang, Bo, et autres
Publié: (2025)

KIT's Offline Speech Translation and Instruction Following Submission for IWSLT 2025
par: Koneru, Sai, et autres
Publié: (2025)

ReplicatorBench: Benchmarking LLM Agents for Replicability in Social and Behavioral Sciences
par: Nguyen, Bang, et autres
Publié: (2026)

Quality-Aware Decoding: Unifying Quality Estimation and Decoding
par: Koneru, Sai, et autres
Publié: (2025)

Retrieval Augmented Instruction Tuning for Open NER with Large Language Models
par: Xie, Tingyu, et autres
Publié: (2024)

Chain-of-Instructions: Compositional Instruction Tuning on Large Language Models
par: Hayati, Shirley Anugrah, et autres
Publié: (2024)

Inside the echo chamber: Linguistic underpinnings of misinformation on Twitter
par: Wang, Xinyu, et autres
Publié: (2024)

Neuron-Aware Data Selection In Instruction Tuning For Large Language Models
par: Chen, Xin, et autres
Publié: (2026)

Plug, Play, and Fuse: Zero-Shot Joint Decoding via Word-Level Re-ranking Across Diverse Vocabularies
par: Koneru, Sai, et autres
Publié: (2024)

Large Language Models can Strategically Deceive their Users when Put Under Pressure
par: Scheurer, Jérémy, et autres
Publié: (2023)

Social Scientists on the Role of AI in Research
par: Chakravorti, Tatiana, et autres
Publié: (2025)

GIFT: Guided Fine-Tuning and Transfer for Enhancing Instruction-Tuned Language Models
par: Ruan, Zhiwen, et autres
Publié: (2026)

GLIDE-RL: Grounded Language Instruction through DEmonstration in RL
par: Kharyal, Chaitanya, et autres
Publié: (2024)

DoG-Instruct: Towards Premium Instruction-Tuning Data via Text-Grounded Instruction Wrapping
par: Chen, Yongrui, et autres
Publié: (2023)

IAPT: Instruction-Aware Prompt Tuning for Large Language Models
par: Zhu, Wei, et autres
Publié: (2024)

Self-Refine Instruction-Tuning for Aligning Reasoning in Language Models
par: Ranaldi, Leonardo, et autres
Publié: (2024)

Dynamics of Instruction Fine-Tuning for Chinese Large Language Models
par: Song, Chiyu, et autres
Publié: (2023)

Dual Instruction Tuning with Large Language Models for Mathematical Reasoning
par: Zhou, Yongwei, et autres
Publié: (2024)

Instructive Decoding: Instruction-Tuned Large Language Models are Self-Refiner from Noisy Instructions
par: Kim, Taehyeon, et autres
Publié: (2023)

Federated Data-Efficient Instruction Tuning for Large Language Models
par: Qin, Zhen, et autres
Publié: (2024)

Wisdom of Instruction-Tuned Language Model Crowds. Exploring Model Label Variation
par: Plaza-del-Arco, Flor Miriam, et autres
Publié: (2023)

Instruction Tuning for Large Language Models: A Survey
par: Zhang, Shengyu, et autres
Publié: (2023)

Hyperparameter Optimization for Large Language Model Instruction-Tuning
par: Tribes, Christophe, et autres
Publié: (2023)

Phased Instruction Fine-Tuning for Large Language Models
par: Pang, Wei, et autres
Publié: (2024)

Investigating Instruction Tuning Large Language Models on Graphs
par: Zhu, Kerui, et autres
Publié: (2024)