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Found 11 papers, 7 papers with code
Baichuan-Audio: A Unified Framework for End-to-End Speech Interaction
To mitigate the loss of intelligence during pre-training and preserve the original capabilities of the LLM, we propose a two-stage pre-training strategy that maintains language understanding while enhancing audio modeling.
Baichuan-M1: Pushing the Medical Capability of Large Language Models
The current generation of large language models (LLMs) is typically designed for broad, general-purpose applications, while domain-specific LLMs, especially in vertical fields like medicine, remain relatively scarce.
Baichuan-Omni-1.5 Technical Report
We introduce Baichuan-Omni-1. 5, an omni-modal model that not only has omni-modal understanding capabilities but also provides end-to-end audio generation capabilities.
Med-R$^2$: Crafting Trustworthy LLM Physicians through Retrieval and Reasoning of Evidence-Based Medicine
In recent years, Large Language Models (LLMs) have exhibited remarkable capabilities in clinical scenarios.
Comprehensive Subjective and Objective Evaluation Method for Text-generated Video
Recent text-to-video (T2V) technology advancements, as demonstrated by models such as Gen3, Pika, and Sora, have significantly broadened its applicability and popularity.
VersaTune: An Efficient Data Composition Framework for Training Multi-Capability LLMs
Despite their potential, existing work mainly focuses on domain-specific enhancements during fine-tuning, the challenge of which lies in catastrophic forgetting of knowledge across other domains.
Baichuan-Omni Technical Report
The salient multimodal capabilities and interactive experience of GPT-4o highlight its critical role in practical applications, yet it lacks a high-performing open-source counterpart.
Ranked #20 on
Visual Question Answering
on MM-Vet
DataSculpt: Crafting Data Landscapes for Long-Context LLMs through Multi-Objective Partitioning
Through extensive experimental analysis, we identified three key challenges in designing effective data management strategies that enable the model to achieve long-context capability without sacrificing performance in other tasks: (1) a shortage of long documents across multiple domains, (2) effective construction of context windows, and (3) efficient organization of large-scale datasets.
BaichuanSEED: Sharing the Potential of ExtensivE Data Collection and Deduplication by Introducing a Competitive Large Language Model Baseline
The general capabilities of Large Language Models (LLM) highly rely on the composition and selection on extensive pretraining datasets, treated as commercial secrets by several institutions.
Baichuan 2: Open Large-scale Language Models
Large language models (LLMs) have demonstrated remarkable performance on a variety of natural language tasks based on just a few examples of natural language instructions, reducing the need for extensive feature engineering.
Blind Predicting Similar Quality Map for Image Quality Assessment
A key problem in blind image quality assessment (BIQA) is how to effectively model the properties of human visual system in a data-driven manner.
Blind Image Quality Assessment
Full reference image quality assessment
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