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From the 1 of 12 linked papers with an AI index.

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12 papers

cs.CV2026

Better, Stronger, Faster, and Broader: Structured All-Mask Prediction for MLLM-Based Segmentation

Jiazhen Liu, Mingkuan Feng, Long Chen

MLLM-based segmentation faces a core segmentation trilemma: high segmentation performance, preserved dialogue ability, and fast inference. Embedding-prediction methods may disrupt…

cs.CV2026

Decoupled Visual Processing: Efficient Multimodal Adaptation via Modality-Specific Transformer Substitution

Mingkuan Feng, Zhengqi Wen, Jianhua Tao

The paper introduces Decoupled Visual Processing, a method that replaces the upper decoder layers of a pretrained language model with a lightweight, trainable transformer block ded…

cs.MA2026

TACO: Tool-Augmented Credit Optimization for Agentic Tool Use

Mingkuan Feng, Jinyang Wu, Hao Gu +5

Agentic multimodal models perform diverse operations on an image via code and reason over the returned view, an effective paradigm for fine-grained visual question answering. Howev…

cs.CL2026

TemplateRL: Structured Template-Guided Reinforcement Learning for LLM Reasoning

Jinyang Wu, Chonghua Liao, Mingkuan Feng +6

Reinforcement learning (RL) has emerged as an effective paradigm for enhancing model reasoning. However, existing RL methods like GRPO typically rely on unstructured self-sampling…

cs.LG2026

Two-Stage Regularization-Based Structured Pruning for LLMs

Mingkuan Feng, Jinyang Wu, Siyuan Liu +7

The deployment of large language models (LLMs) is largely hindered by their large number of parameters. Structural pruning has emerged as a promising solution. Prior structured pru…

cs.CL2026

Exploring Knowledge Purification in Multi-Teacher Knowledge Distillation for LLMs

Ruihan Jin, Pengpeng Shao, Zhengqi Wen +5

Knowledge distillation has emerged as a pivotal technique for transferring knowledge from stronger large language models (LLMs) to smaller, more efficient models. However, traditio…