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Found 10 papers, 6 papers with code
Eagle 2: Building Post-Training Data Strategies from Scratch for Frontier Vision-Language Models
Recently, promising progress has been made by open-source vision-language models (VLMs) in bringing their capabilities closer to those of proprietary frontier models.
Innovative Thinking, Infinite Humor: Humor Research of Large Language Models through Structured Thought Leaps
Humor is a culturally nuanced aspect of human language that presents challenges for understanding and generation, requiring participants to possess good creativity and strong associative thinking.
Eagle: Exploring The Design Space for Multimodal LLMs with Mixture of Encoders
The ability to accurately interpret complex visual information is a crucial topic of multimodal large language models (MLLMs).
MetaTool: Facilitating Large Language Models to Master Tools with Meta-task Augmentation
Training on solution paths is also hindered by the high cost of expert annotations and generalizing to new tools.
PLLaVA : Parameter-free LLaVA Extension from Images to Videos for Video Dense Captioning
PLLaVA achieves new state-of-the-art performance on modern benchmark datasets for both video question-answer and captioning tasks.
ChatAnything: Facetime Chat with LLM-Enhanced Personas
For MoV, we utilize the text-to-speech (TTS) algorithms with a variety of pre-defined tones and select the most matching one based on the user-provided text description automatically.
Multi-grained Evidence Inference for Multi-choice Reading Comprehension
Multi-choice Machine Reading Comprehension (MRC) is a major and challenging task for machines to answer questions according to provided options.
Lite Unified Modeling for Discriminative Reading Comprehension
As a broad and major category in machine reading comprehension (MRC), the generalized goal of discriminative MRC is answer prediction from the given materials.
DocOIE: A Document-level Context-Aware Dataset for OpenIE
Both DocOIE dataset and DocIE model are released for public.
Ranked #1 on
Open Information Extraction
on DocOIE-transportation
Reference Knowledgeable Network for Machine Reading Comprehension
Thus we propose a novel reference-based knowledge enhancement model called Reference Knowledgeable Network (RekNet), which simulates human reading strategies to refine critical information from the passage and quote explicit knowledge in necessity.
