Search Results for author:
Found 10 papers, 7 papers with code
Nova: A Practical and Advanced Alignment
Importantly, Qwen2-Nova-72B and Llama3-PBM-Nova-70B are instruct versions of the Qwen2-72B and Llama-3-70B base models, optimized through Nova.
Facilitating Multi-turn Function Calling for LLMs via Compositional Instruction Tuning
While current research on function calling by LLMs primarily focuses on single-turn interactions, this paper addresses the overlooked necessity for LLMs to engage in multi-turn function calling--critical for handling compositional, real-world queries that require planning with functions but not only use functions.
Ocean-omni: To Understand the World with Omni-modality
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 #13 on
Visual Question Answering
on MM-Vet
Informative Subgraphs Aware Masked Auto-Encoder in Dynamic Graphs
Applying a random masking strategy which most MAE methods adopt to dynamic graphs will remove the crucial subgraph that guides the evolution of dynamic graphs, resulting in the loss of crucial spatio-temporal information in node representations.
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.
MathScape: Evaluating MLLMs in multimodal Math Scenarios through a Hierarchical Benchmark
To address this gap, we proposed MathScape, a new benchmark that emphasizes the understanding and application of combined visual and textual information.
PAS: Data-Efficient Plug-and-Play Prompt Augmentation System
This combination of high performance, efficiency, and flexibility makes PAS a valuable system for enhancing the usability and effectiveness of LLMs through improved prompt engineering.
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.
CFS: A Distributed File System for Large Scale Container Platforms
We propose CFS, a distributed file system for large scale container platforms.
Distributed, Parallel, and Cluster Computing
Rethinking Feature Distribution for Loss Functions in Image Classification
We propose a large-margin Gaussian Mixture (L-GM) loss for deep neural networks in classification tasks.
