29 citations · 82 across the 38 of their papers we have counts for
23 papers · 1 filter
Are Your LLMs Capable of Stable Reasoning?
Junnan Liu, Hongwei Liu, Linchen Xiao +6
The rapid advancement of large language models (LLMs) has shown remarkable progress in complex reasoning tasks. However, a significant disparity exists between benchmark performanc…
CompassJudger-1: All-in-one Judge Model Helps Model Evaluation and Evolution
Maosong Cao, Alexander Lam, Haodong Duan +3
Efficient and accurate evaluation is crucial for the continuous improvement of large language models (LLMs). Among various assessment methods, subjective evaluation has garnered si…
ProSA: Assessing and Understanding the Prompt Sensitivity of LLMs
Jingming Zhuo, Songyang Zhang, Xinyu Fang +3
Large language models (LLMs) have demonstrated impressive capabilities across various tasks, but their performance is highly sensitive to the prompts utilized. This variability pos…
HelloBench: Evaluating Long Text Generation Capabilities of Large Language Models
Haoran Que, Feiyu Duan, Liqun He +11
In recent years, Large Language Models (LLMs) have demonstrated remarkable capabilities in various tasks (e.g., long-context understanding), and many benchmarks have been proposed.…
UrBench: A Comprehensive Benchmark for Evaluating Large Multimodal Models in Multi-View Urban Scenarios
Baichuan Zhou, Haote Yang, Dairong Chen +7
Recent evaluations of Large Multimodal Models (LMMs) have explored their capabilities in various domains, with only few benchmarks specifically focusing on urban environments. More…
LLaST: Improved End-to-end Speech Translation System Leveraged by Large Language Models
Xi Chen, Songyang Zhang, Qibing Bai +2
We introduces LLaST, a framework for building high-performance Large Language model based Speech-to-text Translation systems. We address the limitations of end-to-end speech transl…
InternLM-XComposer-2.5: A Versatile Large Vision Language Model Supporting Long-Contextual Input and Output
Pan Zhang, Xiaoyi Dong, Yuhang Zang +24
We present InternLM-XComposer-2.5 (IXC-2.5), a versatile large-vision language model that supports long-contextual input and output. IXC-2.5 excels in various text-image comprehens…
NeedleBench: Evaluating LLM Retrieval and Reasoning Across Varying Information Densities
Mo Li, Songyang Zhang, Taolin Zhang +3
The capability of large language models to handle long-context information is crucial across various real-world applications. Existing evaluation methods often rely either on real-…
CIBench: Evaluating Your LLMs with a Code Interpreter Plugin
Chuyu Zhang, Songyang Zhang, Yingfan Hu +8
While LLM-Based agents, which use external tools to solve complex problems, have made significant progress, benchmarking their ability is challenging, thereby hindering a clear und…
GTA: A Benchmark for General Tool Agents
Jize Wang, Zerun Ma, Yining Li +4
Significant focus has been placed on integrating large language models (LLMs) with various tools in developing general-purpose agents. This poses a challenge to LLMs' tool-use capa…
InternLM-Law: An Open Source Chinese Legal Large Language Model
Zhiwei Fei, Songyang Zhang, Xiaoyu Shen +9
While large language models (LLMs) have showcased impressive capabilities, they struggle with addressing legal queries due to the intricate complexities and specialized expertise r…
Prism: A Framework for Decoupling and Assessing the Capabilities of VLMs
Yuxuan Qiao, Haodong Duan, Xinyu Fang +6
Vision Language Models (VLMs) demonstrate remarkable proficiency in addressing a wide array of visual questions, which requires strong perception and reasoning faculties. Assessing…
Adapting LLaMA Decoder to Vision Transformer
Jiahao Wang, Wenqi Shao, Mengzhao Chen +7
This work examines whether decoder-only Transformers such as LLaMA, which were originally designed for large language models (LLMs), can be adapted to the computer vision field. We…
MathBench: Evaluating the Theory and Application Proficiency of LLMs with a Hierarchical Mathematics Benchmark
Hongwei Liu, Zilong Zheng, Yuxuan Qiao +7
Recent advancements in large language models (LLMs) have showcased significant improvements in mathematics. However, traditional math benchmarks like GSM8k offer a unidimensional p…
FoundaBench: Evaluating Chinese Fundamental Knowledge Capabilities of Large Language Models
Wei Li, Ren Ma, Jiang Wu +7
In the burgeoning field of large language models (LLMs), the assessment of fundamental knowledge remains a critical challenge, particularly for models tailored to Chinese language…
Ada-LEval: Evaluating long-context LLMs with length-adaptable benchmarks
Chonghua Wang, Haodong Duan, Songyang Zhang +2
Recently, the large language model (LLM) community has shown increasing interest in enhancing LLMs' capability to handle extremely long documents. As various long-text techniques a…
InternLM-XComposer2-4KHD: A Pioneering Large Vision-Language Model Handling Resolutions from 336 Pixels to 4K HD
Xiaoyi Dong, Pan Zhang, Yuhang Zang +21
The Large Vision-Language Model (LVLM) field has seen significant advancements, yet its progression has been hindered by challenges in comprehending fine-grained visual content due…
InternLM2 Technical Report
Zheng Cai, Maosong Cao, Haojiong Chen +97
The evolution of Large Language Models (LLMs) like ChatGPT and GPT-4 has sparked discussions on the advent of Artificial General Intelligence (AGI). However, replicating such advan…
Benchmarking Chinese Commonsense Reasoning of LLMs: From Chinese-Specifics to Reasoning-Memorization Correlations
Jiaxing Sun, Weiquan Huang, Jiang Wu +5
We introduce CHARM, the first benchmark for comprehensively and in-depth evaluating the commonsense reasoning ability of large language models (LLMs) in Chinese, which covers both…
InternLM-Math: Open Math Large Language Models Toward Verifiable Reasoning
Huaiyuan Ying, Shuo Zhang, Linyang Li +19
The math abilities of large language models can represent their abstract reasoning ability. In this paper, we introduce and open-source our math reasoning LLMs InternLM-Math which…
InternLM-XComposer2: Mastering Free-form Text-Image Composition and Comprehension in Vision-Language Large Model
Xiaoyi Dong, Pan Zhang, Yuhang Zang +20
We introduce InternLM-XComposer2, a cutting-edge vision-language model excelling in free-form text-image composition and comprehension. This model goes beyond conventional vision-l…
T-Eval: Evaluating the Tool Utilization Capability of Large Language Models Step by Step
Zehui Chen, Weihua Du, Wenwei Zhang +8
Large language models (LLM) have achieved remarkable performance on various NLP tasks and are augmented by tools for broader applications. Yet, how to evaluate and analyze the tool…
HuixiangDou: Overcoming Group Chat Scenarios with LLM-based Technical Assistance
Huanjun Kong, Songyang Zhang, Jiaying Li +3
In this work, we present HuixiangDou, a technical assistant powered by Large Language Models (LLM). This system is designed to assist algorithm developers by providing insightful r…