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Found 16 papers, 11 papers with code
Bridging the Gap between Training and Inference: Multi-Candidate Optimization for Diverse Neural Machine Translation
Diverse NMT aims at generating multiple diverse yet faithful translations given a source sentence.
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 #6 on
on GPQA
mGTE: Generalized Long-Context Text Representation and Reranking Models for Multilingual Text Retrieval
We first introduce a text encoder (base size) enhanced with RoPE and unpadding, pre-trained in a native 8192-token context (longer than 512 of previous multilingual encoders).
Qwen2 Technical Report
This report introduces the Qwen2 series, the latest addition to our large language models and large multimodal models.
Ranked #1 on
Arithmetic Reasoning
on GSM8K
(using extra training data)
PolyLM: An Open Source Polyglot Large Language Model
Large language models (LLMs) demonstrate remarkable ability to comprehend, reason, and generate following nature language instructions.
Bridging the Domain Gaps in Context Representations for k-Nearest Neighbor Neural Machine Translation
$k$-Nearest neighbor machine translation ($k$NN-MT) has attracted increasing attention due to its ability to non-parametrically adapt to new translation domains.
From Statistical Methods to Deep Learning, Automatic Keyphrase Prediction: A Survey
In this paper, we comprehensively summarize representative studies from the perspectives of dominant models, datasets and evaluation metrics.
WR-ONE2SET: Towards Well-Calibrated Keyphrase Generation
Keyphrase generation aims to automatically generate short phrases summarizing an input document.
CKD-TransBTS: Clinical Knowledge-Driven Hybrid Transformer with Modality-Correlated Cross-Attention for Brain Tumor Segmentation
To bridge the gap between Transformer and CNN features, we propose a Trans&CNN Feature Calibration block (TCFC) in the decoder.
WSSS4LUAD: Grand Challenge on Weakly-supervised Tissue Semantic Segmentation for Lung Adenocarcinoma
According to the technical reports of the top-tier teams, CAM is still the most popular approach in WSSS.
Data Augmentation
Weakly supervised Semantic Segmentation
+1
Multi-Layer Pseudo-Supervision for Histopathology Tissue Semantic Segmentation using Patch-level Classification Labels
In the segmentation phase, we achieved tissue semantic segmentation by our proposed Multi-Layer Pseudo-Supervision.
Towards User-Driven Neural Machine Translation
Furthermore, we contribute the first Chinese-English parallel corpus annotated with user behavior called UDT-Corpus.
Dynamic Context-guided Capsule Network for Multimodal Machine Translation
Particularly, we represent the input image with global and regional visual features, we introduce two parallel DCCNs to model multimodal context vectors with visual features at different granularities.
Ranked #3 on
Multimodal Machine Translation
on Multi30K
Dark Energy Survey Year 1 Results: Cosmological Constraints from Cluster Abundances and Weak Lensing
We perform a joint analysis of the counts and weak lensing signal of redMaPPer clusters selected from the Dark Energy Survey (DES) Year 1 dataset.
Cosmology and Nongalactic Astrophysics
New models for symbolic data analysis
We assume that, as with a standard statistical analysis, inference is required at the level of individual-level data.
Photometric Redshift Error Estimators
Photometric redshift (photo-z) estimates are playing an increasingly important role in extragalactic astronomy and cosmology.
