Search Results for author:
Found 10 papers, 8 papers with code
Rethinking Verification for LLM Code Generation: From Generation to Testing
In addition, we develop a TCGBench to facilitate the study of the TCG task.
OmniAlign-V: Towards Enhanced Alignment of MLLMs with Human Preference
Recent advancements in open-source multi-modal large language models (MLLMs) have primarily focused on enhancing foundational capabilities, leaving a significant gap in human preference alignment.
Condor: Enhance LLM Alignment with Knowledge-Driven Data Synthesis and Refinement
The quality of Supervised Fine-Tuning (SFT) data plays a critical role in enhancing the conversational capabilities of Large Language Models (LLMs).
CompassJudger-1: All-in-one Judge Model Helps Model Evaluation and Evolution
In this report, we introduce \textbf{CompassJudger-1}, the first open-source \textbf{all-in-one} judge LLM.
InternLM-Law: An Open Source Chinese Legal Large Language Model
While large language models (LLMs) have showcased impressive capabilities, they struggle with addressing legal queries due to the intricate complexities and specialized expertise required in the legal field.
InternLM2 Technical Report
The evolution of Large Language Models (LLMs) like ChatGPT and GPT-4 has sparked discussions on the advent of Artificial General Intelligence (AGI).
Ranked #5 on
Long-Context Understanding
on Ada-LEval (BestAnswer)
InternLM-XComposer2: Mastering Free-form Text-Image Composition and Comprehension in Vision-Language Large Model
We introduce InternLM-XComposer2, a cutting-edge vision-language model excelling in free-form text-image composition and comprehension.
Ranked #18 on
Visual Question Answering
on MM-Vet v2
EIPE-text: Evaluation-Guided Iterative Plan Extraction for Long-Form Narrative Text Generation
In this paper, we propose a new framework called Evaluation-guided Iterative Plan Extraction for long-form narrative text generation (EIPE-text), which extracts plans from the corpus of narratives and utilizes the extracted plans to construct a better planner.
Progressive Attention Guidance for Whole Slide Vulvovaginal Candidiasis Screening
Finally, we use a contrastive learning method to alleviate the overfitting caused by the style gap of WSIs and suppress the attention to false positive regions.
CellGAN: Conditional Cervical Cell Synthesis for Augmenting Cytopathological Image Classification
In this paper, we propose CellGAN to synthesize cytopathological images of various cervical cell types for augmenting patch-level cell classification.
