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Found 33 papers, 14 papers with code
Seed1.5-Thinking: Advancing Superb Reasoning Models with Reinforcement Learning
We introduce Seed1. 5-Thinking, capable of reasoning through thinking before responding, resulting in improved performance on a wide range of benchmarks.
Group Reasoning Emission Estimation Networks
To overcome the limitations of single-stage models in handling thousands of hierarchical categories, we propose a Group Reasoning method that ensembles LLM classifiers based on the natural NAICS ontology, decomposing the task into multiple sub-classification steps.
mR$^2$AG: Multimodal Retrieval-Reflection-Augmented Generation for Knowledge-Based VQA
Thus, multimodal Retrieval-Augmented Generation (mRAG) is naturally introduced to provide MLLMs with comprehensive and up-to-date knowledge, effectively expanding the knowledge scope.
Best Practices for Distilling Large Language Models into BERT for Web Search Ranking
Recent studies have highlighted the significant potential of Large Language Models (LLMs) as zero-shot relevance rankers.
Convergence Analysis for Entropy-Regularized Control Problems: A Probabilistic Approach
In this paper we investigate the convergence of the Policy Iteration Algorithm (PIA) for a class of general continuous-time entropy-regularized stochastic control problems.
ExioML: Eco-economic dataset for Machine Learning in Global Sectoral Sustainability
The Environmental Extended Multi-Regional Input-Output analysis is the predominant framework in Ecological Economics for assessing the environmental impact of economic activities.
Non-Intrusive Load Monitoring in Smart Grids: A Comprehensive Review
Non-Intrusive Load Monitoring (NILM) is pivotal in today's energy landscape, offering vital solutions for energy conservation and efficient management.
WebCiteS: Attributed Query-Focused Summarization on Chinese Web Search Results with Citations
Enhancing the attribution in large language models (LLMs) is a crucial task.
CBVS: A Large-Scale Chinese Image-Text Benchmark for Real-World Short Video Search Scenarios
Differently, video covers in short video search scenarios are presented as user-originated contents that provide important visual summaries of videos.
Ranked #1 on
Image Retrieval
on CBVS
Event-driven Real-time Retrieval in Web Search
The Event information is then integrated with the query through a cross-attention mechanism, resulting in a time-context query representation.
Pixel Adapter: A Graph-Based Post-Processing Approach for Scene Text Image Super-Resolution
Additionally, we introduce the MLP-based Sequential Residual Block (MSRB) for robust feature extraction from text images, and a Local Contour Awareness loss ($\mathcal{L}_{lca}$) to enhance the model's perception of details.
Domain Adaptation based Object Detection for Autonomous Driving in Foggy and Rainy Weather
To bridge the domain gap and improve the performance of object detection in foggy and rainy weather, this paper presents a novel framework for domain-adaptive object detection.
DSRM: Boost Textual Adversarial Training with Distribution Shift Risk Minimization
Adversarial training is one of the best-performing methods in improving the robustness of deep language models.
On the Universal Adversarial Perturbations for Efficient Data-free Adversarial Detection
Detecting adversarial samples that are carefully crafted to fool the model is a critical step to socially-secure applications.
Deep Transfer Learning for Intelligent Vehicle Perception: a Survey
To the best of our knowledge, this paper represents the first comprehensive survey on the topic of the deep transfer learning for intelligent vehicle perception.
RXFOOD: Plug-in RGB-X Fusion for Object of Interest Detection
The emergence of different sensors (Near-Infrared, Depth, etc.)
Event-Centric Query Expansion in Web Search
In search engines, query expansion (QE) is a crucial technique to improve search experience.
A Confidence-based Partial Label Learning Model for Crowd-Annotated Named Entity Recognition
Particularly, we propose a Confidence-based Partial Label Learning (CPLL) method to integrate the prior confidence (given by annotators) and posterior confidences (learned by models) for crowd-annotated NER.
T2Ranking: A large-scale Chinese Benchmark for Passage Ranking
T2Ranking comprises more than 300K queries and over 2M unique passages from real-world search engines.
Tagging before Alignment: Integrating Multi-Modal Tags for Video-Text Retrieval
Vision-language alignment learning for video-text retrieval arouses a lot of attention in recent years.
Learning for Vehicle-to-Vehicle Cooperative Perception under Lossy Communication
Due to the beneficial Vehicle-to-Vehicle (V2V) communication, the deep learning based features from other agents can be shared to the ego vehicle so as to improve the perception of the ego vehicle.
Coarse-to-fine Task-driven Inpainting for Geoscience Images
To the best of our knowledge, all the existing image inpainting algorithms learn to repair the occluded regions for a better visualization quality, they are excellent for natural images but not good enough for geoscience images by ignoring the geoscience related tasks.
Title2Event: Benchmarking Open Event Extraction with a Large-scale Chinese Title Dataset
To the best of our knowledge, it is currently the largest manually-annotated Chinese dataset for open event extraction.
Domain Adaptive Object Detection for Autonomous Driving under Foggy Weather
This paper proposes a novel domain adaptive object detection framework for autonomous driving under foggy weather.
ChiQA: A Large Scale Image-based Real-World Question Answering Dataset for Multi-Modal Understanding
However, in most of the public visual question answering datasets such as VQA, CLEVR, the questions are human generated that specific to the given image, such as `What color are her eyes?'.
Boosting Image Outpainting with Semantic Layout Prediction
Secondly, another GAN model is trained to synthesize real images based on the extended semantic layouts.
Out-of-Step Detection Based On an Improved Line Potential Energy Criterion
The line potential energy in the cutset is used as the criterion for monitoring the generator instability, but the criterion has the following two limitations due to narrowly defined conditions.
Research on False Data Injection Attacks in VSC-HVDC Systems
Firstly, the general form of the model of FDI attack strategies is proposed and the essence of the problem of FDI attack strategies is further analyzed.
IPRE: a Dataset for Inter-Personal Relationship Extraction
Our data is the first dataset for inter-personal relationship extraction.
Bayesian Optimized Continual Learning with Attention Mechanism
Though neural networks have achieved much progress in various applications, it is still highly challenging for them to learn from a continuous stream of tasks without forgetting.
Suction Grasp Region Prediction using Self-supervised Learning for Object Picking in Dense Clutter
This paper focuses on robotic picking tasks in cluttered scenario.
Deep Feature Aggregation and Image Re-ranking with Heat Diffusion for Image Retrieval
We show that by considering each deep feature as a heat source, our unsupervised aggregation method is able to avoid over-representation of \emph{bursty} features.
Fast Stability Scanning for Future Grid Scenario Analysis
Future grid scenario analysis requires a major departure from conventional power system planning, where only a handful of most critical conditions is typically analyzed.
