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Found 16 papers, 6 papers with code
BECAME: BayEsian Continual Learning with Adaptive Model MErging
To validate our approach, we introduce a two-stage framework named BECAME, which synergizes the expertise of gradient projection and adaptive merging.
Machine Learning-Based Genomic Linguistic Analysis (Gene Sequence Feature Learning): A Case Study on Predicting Heavy Metal Response Genes in Rice
This study explores the application of machine learning-based genetic linguistics for identifying heavy metal response genes in rice (Oryza sativa).
Qwen2.5-1M Technical Report
By leveraging our inference framework, the Qwen2. 5-1M models achieve a remarkable 3x to 7x prefill speedup in scenarios with 1 million tokens of context.
Qwen2.5 Technical Report
In addition, for hosted solutions, the proprietary models currently include two mixture-of-experts (MoE) variants: Qwen2. 5-Turbo and Qwen2. 5-Plus, both available from Alibaba Cloud Model Studio.
Ranked #7 on
on GPQA
KAAE: Numerical Reasoning for Knowledge Graphs via Knowledge-aware Attributes Learning
Numerical reasoning is pivotal in various artificial intelligence applications, such as natural language processing and recommender systems, where it involves using entities, relations, and attribute values (e. g., weight, length) to infer new factual relations (e. g., the Nile is longer than the Amazon).
NT-LLM: A Novel Node Tokenizer for Integrating Graph Structure into Large Language Models
Graphs are a fundamental data structure for representing relationships in real-world scenarios.
SciSafeEval: A Comprehensive Benchmark for Safety Alignment of Large Language Models in Scientific Tasks
To address these limitations, we introduce SciSafeEval, a comprehensive benchmark designed to evaluate the safety alignment of LLMs across a range of scientific tasks.
Towards Non-invasive and Personalized Management of Breast Cancer Patients from Multiparametric MRI via A Large Mixture-of-Modality-Experts Model
MOME exemplifies a discriminative, robust, scalable, and interpretable multimodal model, paving the way for noninvasive, personalized management of breast cancer patients based on multiparametric breast imaging data.
Qwen2 Technical Report
This report introduces the Qwen2 series, the latest addition to our large language models and large multimodal models.
Ranked #3 on
Arithmetic Reasoning
on GSM8K
(using extra training data)
Qwen Technical Report
Large language models (LLMs) have revolutionized the field of artificial intelligence, enabling natural language processing tasks that were previously thought to be exclusive to humans.
Ranked #3 on
Multi-Label Text Classification
on CC3M-TagMask
PolyLM: An Open Source Polyglot Large Language Model
Large language models (LLMs) demonstrate remarkable ability to comprehend, reason, and generate following nature language instructions.
iEmoTTS: Toward Robust Cross-Speaker Emotion Transfer and Control for Speech Synthesis based on Disentanglement between Prosody and Timbre
The emotion encoder extracts the identity of emotion type as well as the respective emotion intensity from the mel-spectrogram of input speech.
Toward a Fairness-Aware Scoring System for Algorithmic Decision-Making
Then, we transform the social welfare maximization problem into the risk minimization task in machine learning, and derive a fairness-aware scoring system with the help of mixed integer programming.
Explainable Deep Behavioral Sequence Clustering for Transaction Fraud Detection
To utilize the behavior sequence data, we treat click stream data as event sequence, use time attention based Bi-LSTM to learn the sequence embedding in an unsupervised fashion, and combine them with intuitive features generated by risk experts to form a hybrid feature representation.
PG-GSQL: Pointer-Generator Network with Guide Decoding for Cross-Domain Context-Dependent Text-to-SQL Generation
We pay close attention to the cross-domain context-dependent text-to-SQL generation task, which requires a model to depend on the interaction history and current utterance to generate SQL query.
