Cover Image

UltraIF: Advancing Instruction Following from the Wild

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	An, Kaikai, Sheng, Li, Cui, Ganqu, Si, Shuzheng, Ding, Ning, Cheng, Yu, Chang, Baobao
Format:	Preprint
Published:	2025
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

Aligning Large Language Models to Follow Instructions and Hallucinate Less via Effective Data Filtering
by: Si, Shuzheng, et al.
Published: (2025)

Improving the Robustness of Distantly-Supervised Named Entity Recognition via Uncertainty-Aware Teacher Learning and Student-Student Collaborative Learning
by: Si, Shuzheng, et al.
Published: (2023)

Mitigating Language-Level Performance Disparity in mPLMs via Teacher Language Selection and Cross-lingual Self-Distillation
by: Zhao, Haozhe, et al.
Published: (2024)

GATEAU: Selecting Influential Samples for Long Context Alignment
by: Si, Shuzheng, et al.
Published: (2024)

SANTA: Separate Strategies for Inaccurate and Incomplete Annotation Noise in Distantly-Supervised Named Entity Recognition
by: Si, Shuzheng, et al.
Published: (2023)

MMICL: Empowering Vision-language Model with Multi-Modal In-Context Learning
by: Zhao, Haozhe, et al.
Published: (2023)

WildIFEval: Instruction Following in the Wild
by: Lior, Gili, et al.
Published: (2025)

FaithLens: Detecting and Explaining Faithfulness Hallucination
by: Si, Shuzheng, et al.
Published: (2025)

From Drafts to Answers: Unlocking LLM Potential via Aggregation Fine-Tuning
by: Li, Yafu, et al.
Published: (2025)

Rethinking Semantic Parsing for Large Language Models: Enhancing LLM Performance with Semantic Hints
by: An, Kaikai, et al.
Published: (2024)

Teaching Large Language Models to Maintain Contextual Faithfulness via Synthetic Tasks and Reinforcement Learning
by: Si, Shuzheng, et al.
Published: (2025)

Scalable Efficient Training of Large Language Models with Low-dimensional Projected Attention
by: Lv, Xingtai, et al.
Published: (2024)

WildSci: Advancing Scientific Reasoning from In-the-Wild Literature
by: Liu, Tengxiao, et al.
Published: (2026)

Instructions are all you need: Self-supervised Reinforcement Learning for Instruction Following
by: Ren, Qingyu, et al.
Published: (2025)

Scaling Reasoning, Losing Control: Evaluating Instruction Following in Large Reasoning Models
by: Fu, Tingchen, et al.
Published: (2025)

The Right Time Matters: Data Arrangement Affects Zero-Shot Generalization in Instruction Tuning
by: He, Bingxiang, et al.
Published: (2024)

IOPO: Empowering LLMs with Complex Instruction Following via Input-Output Preference Optimization
by: Zhang, Xinghua, et al.
Published: (2024)

Incentivizing Reasoning for Advanced Instruction-Following of Large Language Models
by: Qin, Yulei, et al.
Published: (2025)

UltraFeedback: Boosting Language Models with Scaled AI Feedback
by: Cui, Ganqu, et al.
Published: (2023)

One-Shot Learning as Instruction Data Prospector for Large Language Models
by: Li, Yunshui, et al.
Published: (2023)

Mastering Text, Code and Math Simultaneously via Fusing Highly Specialized Language Models
by: Ding, Ning, et al.
Published: (2024)

MaXIFE: Multilingual and Cross-lingual Instruction Following Evaluation
by: Liu, Yile, et al.
Published: (2025)

ML-Bench: Evaluating Large Language Models and Agents for Machine Learning Tasks on Repository-Level Code
by: Tang, Xiangru, et al.
Published: (2023)

MUFFIN: Curating Multi-Faceted Instructions for Improving Instruction-Following
by: Lou, Renze, et al.
Published: (2023)

From $f(x)$ and $g(x)$ to $f(g(x))$: LLMs Learn New Skills in RL by Composing Old Ones
by: Yuan, Lifan, et al.
Published: (2025)

RhinoInsight: Improving Deep Research through Control Mechanisms for Model Behavior and Context
by: Lei, Yu, et al.
Published: (2025)

TextBind: Multi-turn Interleaved Multimodal Instruction-following in the Wild
by: Li, Huayang, et al.
Published: (2023)

The Instruction Gap: LLMs get lost in Following Instruction
by: Tripathi, Vishesh, et al.
Published: (2025)

Beyond Instruction Following: Evaluating Inferential Rule Following of Large Language Models
by: Sun, Wangtao, et al.
Published: (2024)

Enhancing and Assessing Instruction-Following with Fine-Grained Instruction Variants
by: Yang, Jiuding, et al.
Published: (2024)

Can Language Models Follow Multiple Turns of Entangled Instructions?
by: Han, Chi, et al.
Published: (2025)

Advancing LLM Reasoning Generalists with Preference Trees
by: Yuan, Lifan, et al.
Published: (2024)

Training with Pseudo-Code for Instruction Following
by: Kumar, Prince, et al.
Published: (2025)

VerIF: Verification Engineering for Reinforcement Learning in Instruction Following
by: Peng, Hao, et al.
Published: (2025)

OctoBench: Benchmarking Scaffold-Aware Instruction Following in Repository-Grounded Agentic Coding
by: Ding, Deming, et al.
Published: (2026)

Learning to Reason under Off-Policy Guidance
by: Yan, Jianhao, et al.
Published: (2025)

LIFEBench: Evaluating Length Instruction Following in Large Language Models
by: Zhang, Wei, et al.
Published: (2025)

Benchmarking Complex Instruction-Following with Multiple Constraints Composition
by: Wen, Bosi, et al.
Published: (2024)

InFi-Check: Interpretable and Fine-Grained Fact-Checking of LLMs
by: Bai, Yuzhuo, et al.
Published: (2026)

M-IFEval: Multilingual Instruction-Following Evaluation
by: Dussolle, Antoine, et al.
Published: (2025)