activity
20242026
most citedThe Amazon Nova Family of Models: Technical Report and Model Card

2 citations · 6 across the 11 of their papers we have counts for

collaborators

15 papers

cs.AI2026

Neuro-Symbolic Verification on Instruction Following of LLMs

Yiming Su, Kunzhao Xu, Yanjie Gao +4

A fundamental problem of applying Large Language Models (LLMs) to important applications is that LLMs do not always follow instructions, and violations are often hard to observe or…

cs.IR2025

Meta Lattice: Model Space Redesign for Cost-Effective Industry-Scale Ads Recommendations

Liang Luo, Yuxin Chen, Zhengyu Zhang +39

The rapidly evolving landscape of products, surfaces, policies, and regulations poses significant challenges for deploying state-of-the-art recommendation models at industry scale,…

cs.CR2025

Safe2Harm: Semantic Isomorphism Attacks for Jailbreaking Large Language Models

Fan Yang

Large Language Models (LLMs) have demonstrated exceptional performance across various tasks, but their security vulnerabilities can be exploited by attackers to generate harmful co…

cs.LG20251 cited

Catastrophic Forgetting in Kolmogorov-Arnold Networks

Mohammad Marufur Rahman, Guanchu Wang, Kaixiong Zhou +2

Catastrophic forgetting is a longstanding challenge in continual learning, where models lose knowledge from earlier tasks when learning new ones. While various mitigation strategie…

cs.CV2025

FilmSceneDesigner: Chaining Set Design for Procedural Film Scene Generation

Zhifeng Xie, Keyi Zhang, Yiye Yan +4

Film set design plays a pivotal role in cinematic storytelling and shaping the visual atmosphere. However, the traditional process depends on expert-driven manual modeling, which i…

cs.CL2025

JT-Safe: Intrinsically Enhancing the Safety and Trustworthiness of LLMs

Junlan Feng, Fanyu Meng, Chong Long +12

The hallucination and credibility concerns of large language models (LLMs) are global challenges that the industry is collectively addressing. Recently, a significant amount of adv…