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20242026
most citedA Multimodal Benchmark Dataset and Model for Crop Disease Diagnosis

18 citations · 25 across the 28 of their papers we have counts for

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15 papers · 1 filter

cs.CV2025

LeMiCa: Lexicographic Minimax Path Caching for Efficient Diffusion-Based Video Generation

Huanlin Gao, Ping Chen, Fuyuan Shi +5

We present LeMiCa, a training-free and efficient acceleration framework for diffusion-based video generation. While existing caching strategies primarily focus on reducing local he…

cs.CV2025

HiMo-CLIP: Modeling Semantic Hierarchy and Monotonicity in Vision-Language Alignment

Ruijia Wu, Ping Chen, Fei Shen +8

Contrastive vision-language models like CLIP have achieved impressive results in image-text retrieval by aligning image and text representations in a shared embedding space. Howeve…

cs.CV2025

PSTF-AttControl: Per-Subject-Tuning-Free Personalized Image Generation with Controllable Face Attributes

Xiang liu, Zhaoxiang Liu, Huan Hu +5

Recent advancements in personalized image generation have significantly improved facial identity preservation, particularly in fields such as entertainment and social media. Howeve…

cs.CL2025

Fuzzy Reasoning Chain (FRC): An Innovative Reasoning Framework from Fuzziness to Clarity

Ping Chen, Xiang Liu, Zhaoxiang Liu +7

With the rapid advancement of large language models (LLMs), natural language processing (NLP) has achieved remarkable progress. Nonetheless, significant challenges remain in handli…

cs.CV2025

MITS: A Large-Scale Multimodal Benchmark Dataset for Intelligent Traffic Surveillance

Kaikai Zhao, Zhaoxiang Liu, Peng Wang +7

General-domain large multimodal models (LMMs) have achieved significant advances in various image-text tasks. However, their performance in the Intelligent Traffic Surveillance (IT…

cs.HC2025

iLearnRobot: An Interactive Learning-Based Multi-Modal Robot with Continuous Improvement

Kohou Wang, ZhaoXiang Liu, Lin Bai +5

It is crucial that robots' performance can be improved after deployment, as they are inherently likely to encounter novel scenarios never seen before. This paper presents an innova…

cs.LG2025

Quantitative Analysis of Performance Drop in DeepSeek Model Quantization

Enbo Zhao, Yi Shen, Shuming Shi +7

Recently, there is a high demand for deploying DeepSeek-R1 and V3 locally, possibly because the official service often suffers from being busy and some organizations have data priv…

cs.CL2025

SLearnLLM: A Self-Learning Framework for Efficient Domain-Specific Adaptation of Large Language Models

Xiang Liu, Zhaoxiang Liu, Peng Wang +4

When using supervised fine-tuning (SFT) to adapt large language models (LLMs) to specific domains, a significant challenge arises: should we use the entire SFT dataset for fine-tun…

cs.CV2025★ 3 cited

A Large Vision-Language Model based Environment Perception System for Visually Impaired People

Zezhou Chen, Zhaoxiang Liu, Kai Wang +2

It is a challenging task for visually impaired people to perceive their surrounding environment due to the complexity of the natural scenes. Their personal and social activities ar…

cs.CV2025

Optimizing for the Shortest Path in Denoising Diffusion Model

Ping Chen, Xingpeng Zhang, Zhaoxiang Liu +6

In this research, we propose a novel denoising diffusion model based on shortest-path modeling that optimizes residual propagation to enhance both denoising efficiency and quality.…

cs.CV2025★ 18 cited

A Multimodal Benchmark Dataset and Model for Crop Disease Diagnosis

Xiang Liu, Zhaoxiang Liu, Huan Hu +4

While conversational generative AI has shown considerable potential in enhancing decision-making for agricultural professionals, its exploration has predominantly been anchored in…

cs.CL2025

Safety Evaluation and Enhancement of DeepSeek Models in Chinese Contexts

Wenjing Zhang, Xuejiao Lei, Zhaoxiang Liu +11

DeepSeek-R1, renowned for its exceptional reasoning capabilities and open-source strategy, is significantly influencing the global artificial intelligence landscape. However, it ex…

cs.LG2025

DAST: Difficulty-Adaptive Slow-Thinking for Large Reasoning Models

Yi Shen, Jian Zhang, Jieyun Huang +7

Recent advancements in slow thinking reasoning models have shown exceptional performance in complex reasoning tasks. However, these models often exhibit overthinking (generating re…

cs.AI2025★ 1 cited

Quantifying the Capability Boundary of DeepSeek Models: An Application-Driven Performance Analysis

Kaikai Zhao, Zhaoxiang Liu, Xuejiao Lei +12

DeepSeek-R1, known for its low training cost and exceptional reasoning capabilities, has achieved state-of-the-art performance on various benchmarks. However, detailed evaluations…

cs.CL2025★ 1 cited

Safety Evaluation of DeepSeek Models in Chinese Contexts

Wenjing Zhang, Xuejiao Lei, Zhaoxiang Liu +8

Recently, the DeepSeek series of models, leveraging their exceptional reasoning capabilities and open-source strategy, is reshaping the global AI landscape. Despite these advantage…