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20242026
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6 papers · 1 filter

cs.AI2026

Routing by Reasoning Need: Trajectory-Aware Decoding Control for Diffusion Vision-Language Models

Yixiang Liu, Zhongxing Xu, Zhonghua Wang +1

Diffusion vision-language models generate answers through iterative refinement, exposing intermediate answer trajectories that can be inspected and controlled at inference time. Ho…

cs.AI2026

Why Sample What You Can Enumerate? Exact Policy Optimization for Genomic Tool Selection

Haoyue Liu, Xiaoyu Ma, Ye Chen +2

Reinforcement learning over a frozen reasoner has become a common recipe for teaching a policy which external tools to invoke. We show that this recipe becomes structurally mismatc…

cs.AI2026

Ex-Omni-2D: Expressive Omni-Modal Dialogue Models with Native Visual Presence

Haoyu Zhang, Zhipeng Li, Xiaoying Tang +2

Omni-modal dialogue models can understand multimodal inputs and synthesize spoken replies, but a spoken answer still leaves the agent visually absent. We introduce \textbf{Ex-Omni-…

cs.AI2026

Which Negatives Matter? Ask Your Text Encoder: Adaptive Similarity Margins for Dense-Caption Retrieval

Haoyue Liu, Ye Chen, Zhichao Wang +1

Dense-caption retrieval has recently been improved by introducing segmentation, edge maps, LLM-filtered captions, and cross-modal modules into contrastive fine-tuning. However, the…

cs.AI2026

Are Prompt Optimizers Blind? Cross-Modal Visual Feedback for Automatic Prompt Optimization

Haoyue Liu, Xiaoyu Ma, Ye Chen +2

Automatic prompt optimization (APO) has been widely adopted to adapt vision-language models (VLMs) to downstream tasks without weight updates, yielding promising results. However,…

cs.AI2025

FLEx: Personalized Federated Learning for Mixture-of-Experts LLMs via Expert Grafting

Fan Liu, Bikang Pan, Zhongyi Wang +4

Federated instruction tuning of large language models (LLMs) is challenged by significant data heterogeneity across clients, demanding robust personalization. The Mixture of Expert…