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Found 60 papers, 21 papers with code
Automatic Poetry Generation with Mutual Reinforcement Learning
Human experts evaluate poetry in terms of some specific criteria, instead of word-level likelihood.
Stylistic Chinese Poetry Generation via Unsupervised Style Disentanglement
The ability to write diverse poems in different styles under the same poetic imagery is an important characteristic of human poetry writing.
Jiuge: A Human-Machine Collaborative Chinese Classical Poetry Generation System
By exposing the options of poetry genres, styles and revision modes, Jiuge, acting as a professional assistant, allows constant and active participation of users in poetic creation.
A Dimension-free Algorithm for Contextual Continuum-armed Bandits
The literature has shown that for Lipschitz-continuous functions, the optimal regret is $\tilde{O}(T^{\frac{d_x+d_y+1}{d_x+d_y+2}})$, where $d_x$ and $d_y$ are the dimensions of contexts and arms, and thus suffers from the curse of dimensionality.
Iteratively-Refined Interactive 3D Medical Image Segmentation with Multi-Agent Reinforcement Learning
We here propose to model the dynamic process of iterative interactive image segmentation as a Markov decision process (MDP) and solve it with reinforcement learning (RL).
HMRL: Hyper-Meta Learning for Sparse Reward Reinforcement Learning Problem
In spite of the success of existing meta reinforcement learning methods, they still have difficulty in learning a meta policy effectively for RL problems with sparse reward.
Learning Structured Communication for Multi-agent Reinforcement Learning
This work explores the large-scale multi-agent communication mechanism under a multi-agent reinforcement learning (MARL) setting.
Multi-agent Reinforcement Learning
reinforcement-learning
+1
MixPoet: Diverse Poetry Generation via Learning Controllable Mixed Latent Space
Though recent neural models make prominent progress in some criteria of poetry quality, generated poems still suffer from the problem of poor diversity.
F2A2: Flexible Fully-decentralized Approximate Actor-critic for Cooperative Multi-agent Reinforcement Learning
Traditional centralized multi-agent reinforcement learning (MARL) algorithms are sometimes unpractical in complicated applications, due to non-interactivity between agents, curse of dimensionality and computation complexity.
Multi-agent Reinforcement Learning
Reinforcement Learning (RL)
+2
Dimension Reduction in Contextual Online Learning via Nonparametric Variable Selection
Our algorithm achieves the regret $\tilde{O}(T^{(d_x^*+d_y+1)/(d_x^*+d_y+2)})$, where $d_x^*$ is the effective covariate dimension.
Using Information to Amplify Competition
I characterize the consumer-optimal market segmentation in competitive markets where multiple firms selling differentiated products to consumers with unit demand.
Malicious Requests Detection with Improved Bidirectional Long Short-term Memory Neural Networks
Detecting and intercepting malicious requests are one of the most widely used ways against attacks in the network security.
Structured Diversification Emergence via Reinforced Organization Control and Hierarchical Consensus Learning
In order to improve the efficiency of cooperation and exploration, we propose a structured diversification emergence MARL framework named {\sc{Rochico}} based on reinforced organization control and hierarchical consensus learning.
Dealing with Non-Stationarity in MARL via Trust-Region Decomposition
In this paper, we introduce a novel notion, the $\delta$-measurement, to explicitly measure the non-stationarity of a policy sequence, which can be further proved to be bounded by the KL-divergence of consecutive joint policies.
Exploiting Temporal Contexts with Strided Transformer for 3D Human Pose Estimation
The modified VTE is termed as Strided Transformer Encoder (STE), which is built upon the outputs of VTE.
Ranked #2 on
3D Human Pose Estimation
on HumanEva-I
Weakly-supervised 3D Human Pose Estimation with Cross-view U-shaped Graph Convolutional Network
Instead, exploiting multi-view information is a practical way to achieve absolute 3D human pose estimation.
Monocular 3D Human Pose Estimation
Weakly-supervised 3D Human Pose Estimation
+1
CCPM: A Chinese Classical Poetry Matching Dataset
We hope this dataset can further enhance the study on incorporating deep semantics into the understanding and generation system of Chinese classical poetry.
Interactive Medical Image Segmentation with Self-Adaptive Confidence Calibration
Based on the confidential information, a self-adaptive reward function is designed to provide more detailed feedback, and a simulated label generation mechanism is proposed on unsupervised data to reduce over-reliance on labeled data.
MHFormer: Multi-Hypothesis Transformer for 3D Human Pose Estimation
Estimating 3D human poses from monocular videos is a challenging task due to depth ambiguity and self-occlusion.
Ranked #22 on
3D Human Pose Estimation
on MPI-INF-3DHP
VMAgent: Scheduling Simulator for Reinforcement Learning
A novel simulator called VMAgent is introduced to help RL researchers better explore new methods, especially for virtual machine scheduling.
CUGE: A Chinese Language Understanding and Generation Evaluation Benchmark
We argue that for general-purpose language intelligence evaluation, the benchmark itself needs to be comprehensive and systematic.
Multi-Agent Path Finding with Prioritized Communication Learning
The learning-based, fully decentralized framework has been introduced to alleviate real-time problems and simultaneously pursue optimal planning policy.
Multi-Agent Path Finding
Multi-agent Reinforcement Learning
+1
StyleBERT: Chinese pretraining by font style information
With the success of down streaming task using English pre-trained language model, the pre-trained Chinese language model is also necessary to get a better performance of Chinese NLP task.
GraphMLP: A Graph MLP-Like Architecture for 3D Human Pose Estimation
To the best of our knowledge, this is the first MLP-Like architecture for 3D human pose estimation in a single frame and a video sequence.
Ranked #53 on
3D Human Pose Estimation
on Human3.6M
Fuse It More Deeply! A Variational Transformer with Layer-Wise Latent Variable Inference for Text Generation
The past several years have witnessed Variational Auto-Encoder's superiority in various text generation tasks.
Recurrence Boosts Diversity! Revisiting Recurrent Latent Variable in Transformer-Based Variational AutoEncoder for Diverse Text Generation
We demonstrate that TRACE could enhance the entanglement of each segment and preceding latent variables and deduce a non-zero lower bound of the KL term, providing a theoretical guarantee of generation diversity.
Understanding ME? Multimodal Evaluation for Fine-grained Visual Commonsense
Visual commonsense understanding requires Vision Language (VL) models to not only understand image and text but also cross-reference in-between to fully integrate and achieve comprehension of the visual scene described.
Evade the Trap of Mediocrity: Promoting Diversity and Novelty in Text Generation via Concentrating Attention
In this work, we dig into the intrinsic mechanism of this problem and found that sparser attention values in Transformer could improve diversity.
Algorithmic Decision-Making Safeguarded by Human Knowledge
In view of such a conflict, we provide a general analytical framework to study the augmentation of algorithmic decisions with human knowledge: the analyst uses the knowledge to set a guardrail by which the algorithmic decision is clipped if the algorithmic output is out of bound, and seems unreasonable.
Learning Roles with Emergent Social Value Orientations
Social dilemmas can be considered situations where individual rationality leads to collective irrationality.
HTNet: Human Topology Aware Network for 3D Human Pose Estimation
3D human pose estimation errors would propagate along the human body topology and accumulate at the end joints of limbs.
Ranked #34 on
3D Human Pose Estimation
on MPI-INF-3DHP
(AUC metric)
Diverse Policy Optimization for Structured Action Space
We propose a simple and effective RL method, Diverse Policy Optimization (DPO), to model the policies in structured action space as the energy-based models (EBM) by following the probabilistic RL framework.
Feature Completion Transformer for Occluded Person Re-identification
In this paper, different from most previous works that discard the occluded region, we propose a Feature Completion Transformer (FCFormer) to implicitly complement the semantic information of occluded parts in the feature space.
HiNet: Novel Multi-Scenario & Multi-Task Learning with Hierarchical Information Extraction
Multi-scenario & multi-task learning has been widely applied to many recommendation systems in industrial applications, wherein an effective and practical approach is to carry out multi-scenario transfer learning on the basis of the Mixture-of-Expert (MoE) architecture.
GATOR: Graph-Aware Transformer with Motion-Disentangled Regression for Human Mesh Recovery from a 2D Pose
3D human mesh recovery from a 2D pose plays an important role in various applications.
Ranked #146 on
3D Human Pose Estimation
on Human3.6M
Interweaved Graph and Attention Network for 3D Human Pose Estimation
Despite substantial progress in 3D human pose estimation from a single-view image, prior works rarely explore global and local correlations, leading to insufficient learning of human skeleton representations.
Deep Learning for Solving and Estimating Dynamic Macro-Finance Models
We develop a methodology that utilizes deep learning to simultaneously solve and estimate canonical continuous-time general equilibrium models in financial economics.
Information Design in Multi-Agent Reinforcement Learning
To thrive in those environments, the agent needs to influence other agents so their actions become more helpful and less harmful.
Multi-agent Reinforcement Learning
reinforcement-learning
+1
Semantically Aligned Task Decomposition in Multi-Agent Reinforcement Learning
The difficulty of appropriately assigning credit is particularly heightened in cooperative MARL with sparse reward, due to the concurrent time and structural scales involved.
Efficient Cross-Lingual Transfer for Chinese Stable Diffusion with Images as Pivots
IAP optimizes only a separate Chinese text encoder with all other parameters fixed to align Chinese semantics space to the English one in CLIP.
LLMs and the Abstraction and Reasoning Corpus: Successes, Failures, and the Importance of Object-based Representations
Although the state-of-the-art GPT-4 is unable to "reason" perfectly within non-language domains such as the 1D-ARC or a simple ARC subset, our study reveals that the use of object-based representations can significantly improve its reasoning ability.
Negotiated Reasoning: On Provably Addressing Relative Over-Generalization
Recent methods have shown that assigning reasoning ability to agents can mitigate RO algorithmically and empirically, but there has been a lack of theoretical understanding of RO, let alone designing provably RO-free methods.
MCPI: Integrating Multimodal Data for Enhanced Prediction of Compound Protein Interactions
The identification of compound-protein interactions (CPI) plays a critical role in drug screening, drug repurposing, and combination therapy studies.
Temporally-Extended Prompts Optimization for SAM in Interactive Medical Image Segmentation
The Segmentation Anything Model (SAM) has recently emerged as a foundation model for addressing image segmentation.
Allocating Divisible Resources on Arms with Unknown and Random Rewards
We consider a decision maker allocating one unit of renewable and divisible resource in each period on a number of arms.
Joint Adversarial and Collaborative Learning for Self-Supervised Action Recognition
Considering the instance-level discriminative ability, contrastive learning methods, including MoCo and SimCLR, have been adapted from the original image representation learning task to solve the self-supervised skeleton-based action recognition task.
FastLLVE: Real-Time Low-Light Video Enhancement with Intensity-Aware Lookup Table
Experimental results on benchmark datasets demonstrate that our method achieves the State-Of-The-Art (SOTA) performance in terms of both image quality and inter-frame brightness consistency.
Co-Evolution of Pose and Mesh for 3D Human Body Estimation from Video
Despite significant progress in single image-based 3D human mesh recovery, accurately and smoothly recovering 3D human motion from a video remains challenging.
Efficient Planning with Latent Diffusion
We establish the theoretical equivalence between planning in the latent action space and energy-guided sampling with a pretrained diffusion model and incorporate a novel sequence-level exact sampling method.
DiffNAS: Bootstrapping Diffusion Models by Prompting for Better Architectures
Diffusion models have recently exhibited remarkable performance on synthetic data.
Dataset Bias Mitigation in Multiple-Choice Visual Question Answering and Beyond
Vision-language (VL) understanding tasks evaluate models' comprehension of complex visual scenes through multiple-choice questions.
Hourglass Tokenizer for Efficient Transformer-Based 3D Human Pose Estimation
Transformers have been successfully applied in the field of video-based 3D human pose estimation.
Can language agents be alternatives to PPO? A Preliminary Empirical Study On OpenAI Gym
The formidable capacity for zero- or few-shot decision-making in language agents encourages us to pose a compelling question: Can language agents be alternatives to PPO agents in traditional sequential decision-making tasks?
Not All Steps are Equal: Efficient Generation with Progressive Diffusion Models
In the initial stage, a base denoising model is trained to encompass all timesteps.
Complementary Information Mutual Learning for Multimodality Medical Image Segmentation
CIML adopts the idea of addition and removes inter-modal redundant information through inductive bias-driven task decomposition and message passing-based redundancy filtering.
Exploring Large Language Model based Intelligent Agents: Definitions, Methods, and Prospects
Intelligent agents stand out as a potential path toward artificial general intelligence (AGI).
Uncertainty-Aware Testing-Time Optimization for 3D Human Pose Estimation
We observe that previous optimization-based methods commonly rely on projection constraint, which only ensures alignment in 2D space, potentially leading to the overfitting problem.
Learning Dual-arm Object Rearrangement for Cartesian Robots
To achieve the goal, the core idea is to develop an effective object-to-arm task assignment strategy for minimizing the cumulative task execution time and maximizing the dual-arm cooperation efficiency.
InterFusion: Text-Driven Generation of 3D Human-Object Interaction
In this study, we tackle the complex task of generating 3D human-object interactions (HOI) from textual descriptions in a zero-shot text-to-3D manner.
