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Found 24 papers, 11 papers with code
Beyond Chemical QA: Evaluating LLM's Chemical Reasoning with Modular Chemical Operations
While large language models (LLMs) with Chain-of-Thought (CoT) reasoning excel in mathematics and coding, their potential for systematic reasoning in chemistry, a domain demanding rigorous structural analysis for real-world tasks like drug design and reaction engineering, remains untapped.
Rethinking Text-based Protein Understanding: Retrieval or LLM?
In recent years, protein-text models have gained significant attention for their potential in protein generation and understanding.
Enhanced Sampling, Public Dataset and Generative Model for Drug-Protein Dissociation Dynamics
We propose an enhanced sampling strategy to efficiently implement the drug-protein dissociation process in MD simulations and estimate the free energy surface (FES).
SentiFormer: Metadata Enhanced Transformer for Image Sentiment Analysis
As more and more internet users post images online to express their daily emotions, image sentiment analysis has attracted increasing attention.
ExLM: Rethinking the Impact of [MASK] Tokens in Masked Language Models
This enhancement increases context capacity and enables the model to capture richer semantic information, effectively mitigating the corrupted semantics problem during pre-training.
IPP-Net: A Generalizable Deep Neural Network Model for Indoor Pathloss Radio Map Prediction
In this paper, we propose a generalizable deep neural network model for indoor pathloss radio map prediction (termed as IPP-Net).
SMI-Editor: Edit-based SMILES Language Model with Fragment-level Supervision
SMILES, a crucial textual representation of molecular structures, has garnered significant attention as a foundation for pre-trained language models (LMs).
An accelerate Prediction Strategy for Dynamic Multi-Objective Optimization
To effectively track the changes in the PS and PF in both decision and objective spaces, we propose an adaptive prediction strategy that incorporates second-order derivatives to predict and adjust the algorithms search behavior.
Dynamic 2D Gaussians: Geometrically accurate radiance fields for dynamic objects
In this paper, we propose a novel representation that can reconstruct accurate meshes from sparse image input, named Dynamic 2D Gaussians (D-2DGS).
Causality-inspired Discriminative Feature Learning in Triple Domains for Gait Recognition
Gait recognition is a biometric technology that distinguishes individuals by their walking patterns.
LiCAF: LiDAR-Camera Asymmetric Fusion for Gait Recognition
Gait recognition is a biometric technology that identifies individuals by using walking patterns.
Skim then Focus: Integrating Contextual and Fine-grained Views for Repetitive Action Counting
The key to action counting is accurately locating each video's repetitive actions.
SmoothQuant+: Accurate and Efficient 4-bit Post-Training WeightQuantization for LLM
Our results show that, with SmoothQuant+, the Code Llama-34B model can be quantized and deployed on a A100 40GB GPU, achieving lossless accuracy and a throughput increase of 1. 9 to 4. 0 times compared to the FP16 model deployed on two A100 40GB GPUs.
Condition-Adaptive Graph Convolution Learning for Skeleton-Based Gait Recognition
Graph convolutional networks have been widely applied in skeleton-based gait recognition.
GaitGS: Temporal Feature Learning in Granularity and Span Dimension for Gait Recognition
Gait recognition, a growing field in biological recognition technology, utilizes distinct walking patterns for accurate individual identification.
Robust Dancer: Long-term 3D Dance Synthesis Using Unpaired Data
How to automatically synthesize natural-looking dance movements based on a piece of music is an incrementally popular yet challenging task.
Graph Contrastive Learning for Skeleton-based Action Recognition
In this paper, we propose a graph contrastive learning framework for skeleton-based action recognition (\textit{SkeletonGCL}) to explore the \textit{global} context across all sequences.
Ranked #18 on
Skeleton Based Action Recognition
on NTU RGB+D
Multi-scale Context-aware Network with Transformer for Gait Recognition
Although gait recognition has drawn increasing research attention recently, since the silhouette differences are quite subtle in spatial domain, temporal feature representation is crucial for gait recognition.
Ranked #3 on
Gait Recognition
on OUMVLP
Tracking Instances as Queries
Recently, query based deep networks catch lots of attention owing to their end-to-end pipeline and competitive results on several fundamental computer vision tasks, such as object detection, semantic segmentation, and instance segmentation.
Instances as Queries
The key insight of QueryInst is to leverage the intrinsic one-to-one correspondence in object queries across different stages, as well as one-to-one correspondence between mask RoI features and object queries in the same stage.
Ranked #13 on
Object Detection
on COCO-O
Crossover Learning for Fast Online Video Instance Segmentation
For temporal information modeling in VIS, we present a novel crossover learning scheme that uses the instance feature in the current frame to pixel-wisely localize the same instance in other frames.
Ranked #29 on
Video Instance Segmentation
on YouTube-VIS validation
Deep multi-metric learning for text-independent speaker verification
Text-independent speaker verification is an important artificial intelligence problem that has a wide spectrum of applications, such as criminal investigation, payment certification, and interest-based customer services.
Maximum Entropy Regularization and Chinese Text Recognition
Chinese text recognition is more challenging than Latin text due to the large amount of fine-grained Chinese characters and the great imbalance over classes, which causes a serious overfitting problem.
Patch Aggregator for Scene Text Script Identification
Script identification in the wild is of great importance in a multi-lingual robust-reading system.
