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20202026
most citedLanguage Is Not All You Need: Aligning Perception with Language Models

164 citations · 458 across the 21 of their papers we have counts for

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14 papers · 1 filter

cs.CL2026

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…

cs.CL2025

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…

cs.CL2025

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…

cs.CL2025

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…

cs.CL2024★ 1 cited

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…

cs.CL2024

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…

cs.CL2023★ 8 cited

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…

cs.CL2023★ 164 cited

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…

cs.CL2022★ 32 cited

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…

cs.CL2021★ 35 cited

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.…

cs.CL2021★ 77 cited

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…

cs.CL2021★ 3 cited

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…

cs.CL2021★ 50 cited

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…

cs.CL2020★ 59 cited

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…