From the 1 of 6 linked papers with an AI index.
6 papers
Conan-embedding-v3: Fusing Modality-Specific Models for Omni-Modal Embedding
Shiyu Li, Zhiyuan Hu, Yifan Wang +3
The paper presents Conan-embedding-v3, a framework that trains modality‑specific specialist models, fuses them into a single dense backbone, and then recovers the modality projecto…
ProLaViT: Learning Progressive Latent Visual Thoughts in Structured Latent Space
Peiming Li, Yifan Wang, Xiaotian Zhang +4
Multimodal Large Language Models (MLLMs) have achieved remarkable progress but still struggle with complex visual reasoning tasks requiring multi-step perception and logical deduct…
Focus When Necessary: Adaptive Routing and Collaborative Grounding for Training-Free Visual Grounding
Yifan Wang, Peiming Li, Shiyu Li +5
While Multimodal Large Language Models (MLLMs) excel in cross-modal reasoning, they often struggle to perceive fine-grained details in complex high-resolution images. Recent traini…
Aligning Deep Implicit Preferences by Learning to Reason Defensively
Peiming Li, Zhiyuan Hu, Yang Tang +2
Personalized alignment is crucial for enabling Large Language Models (LLMs) to engage effectively in user-centric interactions. However, current methods face a dual challenge: they…
Render-of-Thought: Rendering Textual Chain-of-Thought as Images for Visual Latent Reasoning
Yifan Wang, Shiyu Li, Peiming Li +3
Chain-of-Thought (CoT) prompting has achieved remarkable success in unlocking the reasoning capabilities of Large Language Models (LLMs). Although CoT prompting enhances reasoning,…
ReSeek: A Self-Correcting Framework for Search Agents with Instructive Rewards
Shiyu Li, Yang Tang, Yifan Wang +2
Search agents powered by Large Language Models (LLMs) have demonstrated significant potential in tackling knowledge-intensive tasks. Reinforcement learning (RL) has emerged as a po…