activity
20222026
most citedPrinciple-Driven Self-Alignment of Language Models from Scratch with Minimal Human Supervision

63 citations · 153 across the 15 of their papers we have counts for

collaborators
Showing cs.LGShow all

6 papers · 1 filter

cs.LG2025

SPL-LNS: Sampling-Enhanced Large Neighborhood Search for Solving Integer Linear Programs

Shengyu Feng, Zhiqing Sun, Yiming Yang

Large Neighborhood Search (LNS) is a common heuristic in combinatorial optimization that iteratively searches over a large neighborhood of the current solution for a better one. Re…

cs.LG2024★ 12 cited

Self-Play Preference Optimization for Language Model Alignment

Yue Wu, Zhiqing Sun, Huizhuo Yuan +3

Standard reinforcement learning from human feedback (RLHF) approaches relying on parametric models like the Bradley-Terry model fall short in capturing the intransitivity and irrat…

cs.LG2024★ 1 cited

Easy-to-Hard Generalization: Scalable Alignment Beyond Human Supervision

Zhiqing Sun, Longhui Yu, Yikang Shen +4

Current AI alignment methodologies rely on human-provided demonstrations or judgments, and the learned capabilities of AI systems would be upper-bounded by human capabilities as a…

cs.LG2023★ 63 cited

Principle-Driven Self-Alignment of Language Models from Scratch with Minimal Human Supervision

Zhiqing Sun, Yikang Shen, Qinhong Zhou +5

Recent AI-assistant agents, such as ChatGPT, predominantly rely on supervised fine-tuning (SFT) with human annotations and reinforcement learning from human feedback (RLHF) to alig…

cs.LG2023★ 1 cited

A Neural PDE Solver with Temporal Stencil Modeling

Zhiqing Sun, Yiming Yang, Shinjae Yoo

Numerical simulation of non-linear partial differential equations plays a crucial role in modeling physical science and engineering phenomena, such as weather, climate, and aerodyn…

cs.LG2022★ 16 cited

DIMES: A Differentiable Meta Solver for Combinatorial Optimization Problems

Ruizhong Qiu, Zhiqing Sun, Yiming Yang

Recently, deep reinforcement learning (DRL) models have shown promising results in solving NP-hard Combinatorial Optimization (CO) problems. However, most DRL solvers can only scal…