activity
20242026
most citedGroot: Adversarial Testing for Generative Text-to-Image Models with Tree-based Semantic Transformation

3 citations · 6 across the 8 of their papers we have counts for

collaborators

8 papers

cs.LG2026★ 1 cited

GLM-5: from Vibe Coding to Agentic Engineering

GLM-5-Team, :, Aohan Zeng +184

We present GLM-5, a next-generation foundation model designed to transition the paradigm of vibe coding to agentic engineering. Building upon the agentic, reasoning, and coding (AR…

cs.SE2026★ 1 cited

The Llama 4 Herd: Architecture, Training, Evaluation, and Deployment Notes

Redacted by arXiv

This document consolidates publicly reported technical details about Metas Llama 4 model family. It summarizes (i) released variants (Scout and Maverick) and the broader herd conte…

cs.LG2026

Self-Distilled Reasoner: On-Policy Self-Distillation for Large Language Models

Siyan Zhao, Zhihui Xie, Mengchen Liu +4

Knowledge distillation improves large language model (LLM) reasoning by compressing the knowledge of a teacher LLM to train smaller LLMs. On-policy distillation advances this appro…

cs.CL2025

TermGPT: Multi-Level Contrastive Fine-Tuning for Terminology Adaptation in Legal and Financial Domain

Yidan Sun, Mengying Zhu, Feiyue Chen +5

Large language models (LLMs) have demonstrated impressive performance in text generation tasks; however, their embedding spaces often suffer from the isotropy problem, resulting in…

cs.CL2025

SPG: Sandwiched Policy Gradient for Masked Diffusion Language Models

Chenyu Wang, Paria Rashidinejad, DiJia Su +9

Diffusion large language models (dLLMs) are emerging as an efficient alternative to autoregressive models due to their ability to decode multiple tokens in parallel. However, align…

cs.LG2025

Inpainting-Guided Policy Optimization for Diffusion Large Language Models

Siyan Zhao, Mengchen Liu, Jing Huang +8

Masked diffusion large language models (dLLMs) are emerging as promising alternatives to autoregressive LLMs, offering competitive performance while supporting unique generation ca…

cs.LG2025★ 1 cited

Recent Advances of NeuroDiffEq -- An Open-Source Library for Physics-Informed Neural Networks

Shuheng Liu, Pavlos Protopapas, David Sondak +1

Solving differential equations is a critical challenge across a host of domains. While many software packages efficiently solve these equations using classical numerical approaches…

cs.CL2024★ 3 cited

Groot: Adversarial Testing for Generative Text-to-Image Models with Tree-based Semantic Transformation

Yi Liu, Guowei Yang, Gelei Deng +5

With the prevalence of text-to-image generative models, their safety becomes a critical concern. adversarial testing techniques have been developed to probe whether such models can…