23 citations · 54 across the 19 of their papers we have counts for
20 papers
DeepSeek-V4.1-Flash: Pushing the Limits of KV Cache Compression
DeepSeek-AI, :, Anyi Xu +585
The widespread adoption of long-horizon agents has made model workloads increasingly input-heavy. Although prior work has substantially reduced the cost of long-context computation…
CPMobius: Iterative Coach-Player Reasoning for Data-Free Reinforcement Learning
Ran Li, Zeyuan Liu, Yinghao Chen +8
Large Language Models (LLMs) have demonstrated strong potential in complex reasoning, yet their progress remains fundamentally constrained by reliance on massive high-quality human…
EmbodiedEval: Evaluate Multimodal LLMs as Embodied Agents
Zhili Cheng, Yuge Tu, Ran Li +9
Multimodal Large Language Models (MLLMs) have shown significant advancements, providing a promising future for embodied agents. Existing benchmarks for evaluating MLLMs primarily u…
Euclid: Supercharging Multimodal LLMs with Synthetic High-Fidelity Visual Descriptions
Jiarui Zhang, Ollie Liu, Tianyu Yu +2
Multimodal large language models (MLLMs) have made rapid progress in recent years, yet continue to struggle with low-level visual perception (LLVP) -- particularly the ability to a…
ACDiT: Interpolating Autoregressive Conditional Modeling and Diffusion Transformer
Jinyi Hu, Shengding Hu, Yuxuan Song +6
Autoregressive and diffusion models have achieved remarkable progress in language models and visual generation, respectively. We present ACDiT, a novel Autoregressive blockwise Con…
AdaNAT: Exploring Adaptive Policy for Token-Based Image Generation
Zanlin Ni, Yulin Wang, Renping Zhou +6
Recent studies have demonstrated the effectiveness of token-based methods for visual content generation. As a representative work, non-autoregressive Transformers (NATs) are able t…
Revisiting Non-Autoregressive Transformers for Efficient Image Synthesis
Zanlin Ni, Yulin Wang, Renping Zhou +6
The field of image synthesis is currently flourishing due to the advancements in diffusion models. While diffusion models have been successful, their computational intensity has pr…
GUICourse: From General Vision Language Models to Versatile GUI Agents
Wentong Chen, Junbo Cui, Jinyi Hu +11
Utilizing Graphic User Interface (GUI) for human-computer interaction is essential for accessing a wide range of digital tools. Recent advancements in Vision Language Models (VLMs)…
LEGENT: Open Platform for Embodied Agents
Zhili Cheng, Zhitong Wang, Jinyi Hu +7
Despite advancements in Large Language Models (LLMs) and Large Multimodal Models (LMMs), their integration into language-grounded, human-like embodied agents remains incomplete, hi…
Exploring Perceptual Limitation of Multimodal Large Language Models
Jiarui Zhang, Jinyi Hu, Mahyar Khayatkhoei +2
Multimodal Large Language Models (MLLMs) have recently shown remarkable perceptual capability in answering visual questions, however, little is known about the limits of their perc…
OlympiadBench: A Challenging Benchmark for Promoting AGI with Olympiad-Level Bilingual Multimodal Scientific Problems
Chaoqun He, Renjie Luo, Yuzhuo Bai +11
Recent advancements have seen Large Language Models (LLMs) and Large Multimodal Models (LMMs) surpassing general human capabilities in various tasks, approaching the proficiency le…
RLHF-V: Towards Trustworthy MLLMs via Behavior Alignment from Fine-grained Correctional Human Feedback
Tianyu Yu, Yuan Yao, Haoye Zhang +8
Multimodal Large Language Models (MLLMs) have recently demonstrated impressive capabilities in multimodal understanding, reasoning, and interaction. However, existing MLLMs prevale…
Reformulating Vision-Language Foundation Models and Datasets Towards Universal Multimodal Assistants
Tianyu Yu, Jinyi Hu, Yuan Yao +10
Recent Multimodal Large Language Models (MLLMs) exhibit impressive abilities to perceive images and follow open-ended instructions. The capabilities of MLLMs depend on two crucial…
Large Multilingual Models Pivot Zero-Shot Multimodal Learning across Languages
Jinyi Hu, Yuan Yao, Chongyi Wang +13
Recently there has been a significant surge in multimodal learning in terms of both image-to-text and text-to-image generation. However, the success is typically limited to English…
Efficient Cross-Lingual Transfer for Chinese Stable Diffusion with Images as Pivots
Jinyi Hu, Xu Han, Xiaoyuan Yi +4
Diffusion models have made impressive progress in text-to-image synthesis. However, training such large-scale models (e.g. Stable Diffusion), from scratch requires high computation…
Recurrence Boosts Diversity! Revisiting Recurrent Latent Variable in Transformer-Based Variational AutoEncoder for Diverse Text Generation
Jinyi Hu, Xiaoyuan Yi, Wenhao Li +2
Variational Auto-Encoder (VAE) has been widely adopted in text generation. Among many variants, recurrent VAE learns token-wise latent variables with each conditioned on the preced…
Evade the Trap of Mediocrity: Promoting Diversity and Novelty in Text Generation via Concentrating Attention
Wenhao Li, Xiaoyuan Yi, Jinyi Hu +2
Recently, powerful Transformer architectures have proven superior in generating high-quality sentences. Nevertheless, these models tend to produce dull high-frequency phrases, seve…
Fuse It More Deeply! A Variational Transformer with Layer-Wise Latent Variable Inference for Text Generation
Jinyi Hu, Xiaoyuan Yi, Wenhao Li +2
The past several years have witnessed Variational Auto-Encoder's superiority in various text generation tasks. However, due to the sequential nature of the text, auto-regressive de…
Towards Interpretable Natural Language Understanding with Explanations as Latent Variables
Wangchunshu Zhou, Jinyi Hu, Hanlin Zhang +4
Recently generating natural language explanations has shown very promising results in not only offering interpretable explanations but also providing additional information and sup…
Generating Major Types of Chinese Classical Poetry in a Uniformed Framework
Jinyi Hu, Maosong Sun
Poetry generation is an interesting research topic in the field of text generation. As one of the most valuable literary and cultural heritages of China, Chinese classical poetry i…