164 citations · 458 across the 21 of their papers we have counts for
22 papers
CART: Closed-Loop Adaptive Red Teaming for Large Language Models
Dongdong Zhang, Tengchao Lv, Yilin Jia +9
Automated red teaming often replays a fixed set of prompts, which measures known risks but cannot learn from failures found during testing. We present CART (Closed-Loop Adaptive Re…
Scaling Data Difficulty: Improving Coding Models via Reinforcement Learning on Fresh and Challenging Problems
Zongqian Li, Tengchao Lv, Shaohan Huang +8
Training next-generation code generation models requires high-quality datasets, yet existing datasets face difficulty imbalance, format inconsistency, and data quality problems. We…
Code Aesthetics with Agentic Reward Feedback
Bang Xiao, Lingjie Jiang, Shaohan Huang +5
Large Language Models (LLMs) have become valuable assistants for developers in code-related tasks. While LLMs excel at traditional programming tasks such as code generation and bug…
DocReward: A Document Reward Model for Structuring and Stylizing
Junpeng Liu, Yuzhong Zhao, Bowen Cao +17
Recent agentic workflows automate professional document generation but focus narrowly on textual quality, overlooking structural and stylistic professionalism, which is equally cri…
Geometric-Mean Policy Optimization
Yuzhong Zhao, Yue Liu, Junpeng Liu +9
Group Relative Policy Optimization (GRPO) has significantly enhanced the reasoning capability of large language models by optimizing the arithmetic mean of token-level rewards. Unf…
Think Only When You Need with Large Hybrid-Reasoning Models
Lingjie Jiang, Xun Wu, Shaohan Huang +7
Recent Large Reasoning Models (LRMs) have shown substantially improved reasoning capabilities over traditional Large Language Models (LLMs) by incorporating extended thinking proce…
Model as a Game: On Numerical and Spatial Consistency for Generative Games
Jingye Chen, Yuzhong Zhao, Yupan Huang +5
Recent advances in generative models have significantly impacted game generation. However, despite producing high-quality graphics and adequately receiving player input, existing m…
PEACE: Empowering Geologic Map Holistic Understanding with MLLMs
Yangyu Huang, Tianyi Gao, Haoran Xu +8
Geologic map, as a fundamental diagram in geology science, provides critical insights into the structure and composition of Earth's subsurface and surface. These maps are indispens…
MMLU-CF: A Contamination-free Multi-task Language Understanding Benchmark
Qihao Zhao, Yangyu Huang, Tengchao Lv +8
Multiple-choice question (MCQ) datasets like Massive Multitask Language Understanding (MMLU) are widely used to evaluate the commonsense, understanding, and problem-solving abiliti…
RedStone: Curating General, Code, Math, and QA Data for Large Language Models
Yaoyao Chang, Lei Cui, Li Dong +13
Pre-training Large Language Models (LLMs) on high-quality, meticulously curated datasets is widely recognized as critical for enhancing their performance and generalization capabil…
TextDiffuser-2: Unleashing the Power of Language Models for Text Rendering
Jingye Chen, Yupan Huang, Tengchao Lv +3
The diffusion model has been proven a powerful generative model in recent years, yet remains a challenge in generating visual text. Several methods alleviated this issue by incorpo…
KOSMOS-2.5: A Multimodal Literate Model
Tengchao Lv, Yupan Huang, Jingye Chen +13
The automatic reading of text-intensive images represents a significant advancement toward achieving Artificial General Intelligence (AGI). In this paper we present KOSMOS-2.5, a m…
TextDiffuser: Diffusion Models as Text Painters
Jingye Chen, Yupan Huang, Tengchao Lv +3
Diffusion models have gained increasing attention for their impressive generation abilities but currently struggle with rendering accurate and coherent text. To address this issue,…
Language Is Not All You Need: Aligning Perception with Language Models
Shaohan Huang, Li Dong, Wenhui Wang +15
A big convergence of language, multimodal perception, action, and world modeling is a key step toward artificial general intelligence. In this work, we introduce Kosmos-1, a Multim…
The Shannon Entropy of a Histogram
Stephen Watts, Lisa Crow
The histogram is a key method for visualizing data and estimating the underlying probability distribution. Incorrect conclusions about the data result from over or under-binning. A…
LayoutLMv3: Pre-training for Document AI with Unified Text and Image Masking
Yupan Huang, Tengchao Lv, Lei Cui +2
Self-supervised pre-training techniques have achieved remarkable progress in Document AI. Most multimodal pre-trained models use a masked language modeling objective to learn bidir…
DiT: Self-supervised Pre-training for Document Image Transformer
Junlong Li, Yiheng Xu, Tengchao Lv +3
Image Transformer has recently achieved significant progress for natural image understanding, either using supervised (ViT, DeiT, etc.) or self-supervised (BEiT, MAE, etc.) pre-tra…
Document AI: Benchmarks, Models and Applications
Lei Cui, Yiheng Xu, Tengchao Lv +1
Document AI, or Document Intelligence, is a relatively new research topic that refers to the techniques for automatically reading, understanding, and analyzing business documents.…
TrOCR: Transformer-based Optical Character Recognition with Pre-trained Models
Minghao Li, Tengchao Lv, Jingye Chen +6
Text recognition is a long-standing research problem for document digitalization. Existing approaches are usually built based on CNN for image understanding and RNN for char-level…
VT-SSum: A Benchmark Dataset for Video Transcript Segmentation and Summarization
Tengchao Lv, Lei Cui, Momcilo Vasilijevic +1
Video transcript summarization is a fundamental task for video understanding. Conventional approaches for transcript summarization are usually built upon the summarization data for…
LayoutXLM: Multimodal Pre-training for Multilingual Visually-rich Document Understanding
Yiheng Xu, Tengchao Lv, Lei Cui +5
Multimodal pre-training with text, layout, and image has achieved SOTA performance for visually-rich document understanding tasks recently, which demonstrates the great potential f…
LayoutLMv2: Multi-modal Pre-training for Visually-Rich Document Understanding
Yang Xu, Yiheng Xu, Tengchao Lv +9
Pre-training of text and layout has proved effective in a variety of visually-rich document understanding tasks due to its effective model architecture and the advantage of large-s…