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20242026
most citedA User-Friendly Framework for Generating Model-Preferred Prompts in Text-to-Image Synthesis

9 citations · 10 across the 15 of their papers we have counts for

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6 papers · 1 filter

cs.CL2026

From Parameters to Behaviors: A Survey of Model Fusion for Large Language Models

Shuo Cai, Yanggan Gu, Zihao Wang +8

Model fusion integrates the capabilities from source models into a single target model. As of June 2026, Hugging Face hosts more than 2M models. This growing pool provides a rich b…

cs.CL2026

DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence

DeepSeek-AI, Anyi Xu, Bangcai Lin +315

We present a preview version of DeepSeek-V4 series, including two strong Mixture-of-Experts (MoE) language models -- DeepSeek-V4-Pro with 1.6T parameters (49B activated) and DeepSe…

cs.DB2026

MergePipe: A Budget-Aware Parameter Management System for Scalable LLM Merging

Yuanyi Wang, Yanggan Gu, Zihao Wang +6

Large language model (LLM) merging has become a key technique in modern LLM development pipelines, enabling the integration of multiple task- or domain-specific expert models witho…

cs.CV2026

Hierarchical Concept-to-Appearance Guidance for Multi-Subject Image Generation

Yijia Xu, Zihao Wang, Haokun Gui +1

Multi-subject image generation aims to synthesize images that faithfully preserve the identities of multiple reference subjects while following textual instructions. However, exist…

cs.AI2026

Do Reasoning Models Enhance Embedding Models?

Wun Yu Chan, Shaojin Chen, Huihao Jing +5

State-of-the-art embedding models are increasingly derived from decoder-only Large Language Model (LLM) backbones adapted via contrastive learning. Given the emergence of reasoning…

cs.LG2026

Dynamic Large Concept Models: Latent Reasoning in an Adaptive Semantic Space

Xingwei Qu, Shaowen Wang, Zihao Huang +16

Large Language Models (LLMs) apply uniform computation to all tokens, despite language exhibiting highly non-uniform information density. This token-uniform regime wastes capacity…