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Found 13 papers, 7 papers with code
Single-Cell Omics Arena: A Benchmark Study for Large Language Models on Cell Type Annotation Using Single-Cell Data
To thoroughly evaluate the capability of modern instruction-tuned LLMs in automating the cell type identification process, we introduce SOAR, a comprehensive benchmarking study of LLMs for cell type annotation tasks in single-cell genomics.
ConLUX: Concept-Based Local Unified Explanations
With the rapid advancements of various machine learning models, there is a significant demand for model-agnostic explanation techniques, which can explain these models across different architectures.
Hierarchical Context Pruning: Optimizing Real-World Code Completion with Repository-Level Pretrained Code LLMs
We applied the HCP strategy in experiments with six Repo-Code LLMs, and the results demonstrate that our proposed method can significantly enhance completion accuracy while substantially reducing the length of input.
One-Shot Learning as Instruction Data Prospector for Large Language Models
Contemporary practices in instruction tuning often hinge on enlarging data scaling without a clear strategy for ensuring data quality, inadvertently introducing noise that may compromise model performance.
Marathon: A Race Through the Realm of Long Context with Large Language Models
With the advancement of large language models (LLMs) and the expansion of their context windows, existing long-context benchmarks fall short in effectively evaluating the models' comprehension and reasoning abilities in extended texts.
Self-Distillation with Meta Learning for Knowledge Graph Completion
In this paper, we propose a selfdistillation framework with meta learning(MetaSD) for knowledge graph completion with dynamic pruning, which aims to learn compressed graph embeddings and tackle the longtail samples.
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ReX: A Framework for Incorporating Temporal Information in Model-Agnostic Local Explanation Techniques
To address this limitation, we propose ReX, a general framework for adapting various explanation techniques to models that process variable-length inputs, expanding explanation coverage to data points of different lengths.
Free Lunch for Co-Saliency Detection: Context Adjustment
We hope that the scale, diversity, and quality of our dataset can benefit researchers in this area and beyond.
Multi-perspective Coherent Reasoning for Helpfulness Prediction of Multimodal Reviews
In addition, we also devise an intra-review coherent reasoning module to identify the coherence between the text content and images of the review, which is a piece of strong evidence for review helpfulness prediction.
DR 21 South Filament: a Parsec-sized Dense Gas Accretion Flow onto the DR 21 Massive Young Cluster
DR21 south filament (DR21SF) is a unique component of the giant network of filamentary molecular clouds in the north region of Cygnus X complex.
Astrophysics of Galaxies
Dual Dynamic Memory Network for End-to-End Multi-turn Task-oriented Dialog Systems
To conquer these limitations, we propose a Dual Dynamic Memory Network (DDMN) for multi-turn dialog generation, which maintains two core components: dialog memory manager and KB memory manager.
Cross-lingual Machine Reading Comprehension with Language Branch Knowledge Distillation
Then, we devise a multilingual distillation approach to amalgamate knowledge from multiple language branch models to a single model for all target languages.
Improving Knowledge-aware Dialogue Generation via Knowledge Base Question Answering
In this paper, we propose a novel knowledge-aware dialogue generation model (called TransDG), which transfers question representation and knowledge matching abilities from knowledge base question answering (KBQA) task to facilitate the utterance understanding and factual knowledge selection for dialogue generation.
