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Alan Ritter

ICML 2026×3ACL 2026CHI 2026推理强化学习与后训练多模态多语言与语言学智能体与工具
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0 一作 · 5 篇 · ICML 2026 / ACL 2026 / CHI 2026

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2026 顶会论文

5
作者位次 #3/3ICML 2026Poster· Deep Learning / Large Language Models

Making Expert Reasoning Learnable with Self-Distillation

Ethan Mendes · Jungsoo Park · Alan Ritter

推理强化学习与后训练OpenReview
作者位次 #4/5ICML 2026Poster· Applications / Language, Speech and Dialog

Learning to Route Languages for Multilingual Policy Optimization

Geyang Guo · Hiromi Wakaki · Yuki Mitsufuji · Alan Ritter · Wei Xu

多模态强化学习与后训练多语言与语言学OpenReview
作者位次 #3/3ICML 2026Poster· Deep Learning / Large Language Models

Safe and Scalable Web Agent Learning via Recreated Websites

Hyungjoo Chae · Jungsoo Park · Alan Ritter

智能体与工具OpenReview
作者位次 #7/9ACL 2026Poster· Natural Language Processing

G eo RC : A Benchmark for Geolocation Reasoning Chains

Mohit Talreja · Joshua Diao · Jim James · Radu Casapu · Tejas Santanam · Ethan Mendes · Alan Ritter · Wei Xu · James Hays

摘要

Vision Language Models (VLMs) are good at recognizing the global location of a photograph – their geolocation prediction accuracy rivals the best human experts. But many VLMs are startlingly bad at explaining which image evidence led to their prediction, even when their location prediction is cor...

多模态评测与基准推理OpenReview 项目页

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