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20242026
most citedMulti-IF: Benchmarking LLMs on Multi-Turn and Multilingual Instructions Following

5 citations · 11 across the 14 of their papers we have counts for

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Showing 2025Show all

7 papers · 1 filter

cs.CV2025

LangDriveCTRL: Natural Language Controllable Driving Scene Editing with Multi-modal Agents

Yun He, Francesco Pittaluga, Ziyu Jiang +3

LangDriveCTRL is a natural-language-controllable framework for editing real-world driving videos to synthesize diverse traffic scenarios. It represents each video as an explicit 3D…

cs.CL2025★ 1 cited

AdvancedIF: Rubric-Based Benchmarking and Reinforcement Learning for Advancing LLM Instruction Following

Yun He, Wenzhe Li, Hejia Zhang +22

Recent progress in large language models (LLMs) has led to impressive performance on a range of tasks, yet advanced instruction following (IF)-especially for complex, multi-turn, a…

cs.LG2025

Bradley-Terry Policy Optimization for Generative Preference Modeling

Shengyu Feng, Yun He, Shuang Ma +12

Reinforcement learning (RL) has recently proven effective at scaling chain-of-thought (CoT) reasoning in large language models for tasks with verifiable answers. However, extending…

cs.AI2025

Generalized Parallel Scaling with Interdependent Generations

Harry Dong, David Brandfonbrener, Eryk Helenowski +5

Parallel LLM inference scaling involves sampling a set of responses for a single input prompt. However, these parallel responses tend to be generated independently from e…

cs.AI2025

Boosting LLM Reasoning via Spontaneous Self-Correction

Xutong Zhao, Tengyu Xu, Xuewei Wang +11

While large language models (LLMs) have demonstrated remarkable success on a broad range of tasks, math reasoning remains a challenging one. One of the approaches for improving mat…

cs.AI2025

Think Smarter not Harder: Adaptive Reasoning with Inference Aware Optimization

Zishun Yu, Tengyu Xu, Di Jin +9

Solving mathematics problems has been an intriguing capability of large language models, and many efforts have been made to improve reasoning by extending reasoning length, such as…

cs.LG2025★ 1 cited

Step-KTO: Optimizing Mathematical Reasoning through Stepwise Binary Feedback

Yen-Ting Lin, Di Jin, Tengyu Xu +11

Large language models (LLMs) have recently demonstrated remarkable success in mathematical reasoning. Despite progress in methods like chain-of-thought prompting and self-consisten…