26 citations · 64 across the 16 of their papers we have counts for
9 papers · 1 filter
MiniCPM-o 4.5: Towards Real-Time Full-Duplex Omni-Modal Interaction
Junbo Cui, Bokai Xu, Chongyi Wang +33
Recent progress in multimodal large language models (MLLMs) has brought AI capabilities from static offline data processing to real-time streaming interaction, yet they still remai…
RLAIF-V: Open-Source AI Feedback Leads to Super GPT-4V Trustworthiness
Tianyu Yu, Haoye Zhang, Qiming Li +13
Traditional feedback learning for hallucination reduction relies on labor-intensive manual labeling or expensive proprietary models. This leaves the community without foundational…
UltraWiki: Ultra-fine-grained Entity Set Expansion with Negative Seed Entities
Yangning Li, Qingsong Lv, Tianyu Yu +5
Entity Set Expansion (ESE) aims to identify new entities belonging to the same semantic class as the given set of seed entities. Traditional methods solely relied on positive seed…
RLHF-V: Towards Trustworthy MLLMs via Behavior Alignment from Fine-grained Correctional Human Feedback
Tianyu Yu, Yuan Yao, Haoye Zhang +8
Multimodal Large Language Models (MLLMs) have recently demonstrated impressive capabilities in multimodal understanding, reasoning, and interaction. However, existing MLLMs prevale…
SeqGPT: An Out-of-the-box Large Language Model for Open Domain Sequence Understanding
Tianyu Yu, Chengyue Jiang, Chao Lou +12
Large language models (LLMs) have shown impressive ability for open-domain NLP tasks. However, LLMs are sometimes too footloose for natural language understanding (NLU) tasks which…
Large Multilingual Models Pivot Zero-Shot Multimodal Learning across Languages
Jinyi Hu, Yuan Yao, Chongyi Wang +13
Recently there has been a significant surge in multimodal learning in terms of both image-to-text and text-to-image generation. However, the success is typically limited to English…
MESED: A Multi-modal Entity Set Expansion Dataset with Fine-grained Semantic Classes and Hard Negative Entities
Yangning Li, Tingwei Lu, Yinghui Li +5
The Entity Set Expansion (ESE) task aims to expand a handful of seed entities with new entities belonging to the same semantic class. Conventional ESE methods are based on mono-mod…
Embracing Ambiguity: Improving Similarity-oriented Tasks with Contextual Synonym Knowledge
Yangning Li, Jiaoyan Chen, Yinghui Li +3
Contextual synonym knowledge is crucial for those similarity-oriented tasks whose core challenge lies in capturing semantic similarity between entities in their contexts, such as e…
Contrastive Learning with Hard Negative Entities for Entity Set Expansion
Yinghui Li, Yangning Li, Yuxin He +3
Entity Set Expansion (ESE) is a promising task which aims to expand entities of the target semantic class described by a small seed entity set. Various NLP and IR applications will…