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Peng Di

ACL 2026×2ICML 2026×2AAAI 2026KDD 2026PPoPP 2026可解释性多模态效率与系统检索与知识代码
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0 一作 · 7 篇 · ACL 2026 / ICML 2026 / AAAI 2026 / KDD 2026 / PPoPP 2026

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2026 顶会论文

7
作者位次 #4/5ICML 2026Poster· Applications / Language, Speech and Dialog

ML-Embed: Inclusive and Efficient Embeddings for a Multilingual World

Ziyin Zhang · Zihan Liao · Hang Yu · Peng Di · Rui Wang

多模态效率与系统多语言与语言学OpenReview
作者位次 #4/4ICML 2026Poster· Deep Learning / Self-Supervised Learning

SOLAR: Self-supervised Joint Learning for Symmetric Multimodal Retrieval

Wenjie Yang · Hang Yu · Yuyu Guo · Peng Di

多模态检索与知识OpenReview
作者位次 #5/6ACL 2026Poster· ACL Industry Track

T ing IS : Real-time Risk Event Discovery from Noisy Customer Incidents at Enterprise Scale

Jun Wang · Ziyin Zhang · Rui Wang · Hang Yu · Peng Di · Rui Wang

摘要

Real-time detection and mitigation of technical anomalies are critical for large-scale cloud-native services, where even minutes of downtime can result in massive financial losses and diminished user trust. While customer incidents serve as a vital signal for discovering risks missed by monitorin...

效率与系统可解释性评测与基准OpenReview 项目页
作者位次 #3/4ACL 2026Findings· Findings of ACL

N- GRPO : Embedding-Level Neighbor Mixing for Enhanced Policy Optimization

Xukun Zhu · Hang Yu · Peng Di · Linchao Zhu

摘要

The success of Large Language Models in mathematical reasoning relies heavily on the generation of diverse and valid solution paths during the rollout phase. However, current rollout techniques face a fundamental trade-off: token-level sampling often yields redundant trajectories that differ only...

强化学习与后训练推理可解释性OpenReview 项目页

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