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Found 22 papers, 12 papers with code
Learning Symmetry-Independent Jet Representations via Jet-Based Joint Embedding Predictive Architecture
In high energy physics, self-supervised learning (SSL) methods have the potential to aid in the creation of machine learning models without the need for labeled datasets for a variety of tasks, including those related to jets -- narrow sprays of particles produced by quarks and gluons in high energy particle collisions.
SEEKR: Selective Attention-Guided Knowledge Retention for Continual Learning of Large Language Models
In this work, we first explore and emphasize the importance of attention weights in knowledge retention, and then propose a SElective attEntion-guided Knowledge Retention method (SEEKR) for data-efficient replay-based continual learning of large language models (LLMs).
SciDFM: A Large Language Model with Mixture-of-Experts for Science
We further analyze the expert layers and show that the results of expert selection vary with data from different disciplines.
ChemDFM-X: Towards Large Multimodal Model for Chemistry
Rapid developments of AI tools are expected to offer unprecedented assistance to the research of natural science including chemistry.
Boosting Medical Image Classification with Segmentation Foundation Model
The Segment Anything Model (SAM) exhibits impressive capabilities in zero-shot segmentation for natural images.
Hierarchical Multimodal Pre-training for Visually Rich Webpage Understanding
Additionally, we propose several pre-training tasks to model the interaction among text, structure, and image modalities effectively.
MULTI: Multimodal Understanding Leaderboard with Text and Images
The rapid development of multimodal large language models (MLLMs) raises the question of how they compare to human performance.
Computational Experiments Meet Large Language Model Based Agents: A Survey and Perspective
These agents, known as LLM-based Agent, offer the potential to enhance the anthropomorphism lacking in ABM.
ChemDFM: A Large Language Foundation Model for Chemistry
In its utmost form, such a generalist AI chemist could be referred to as Chemical General Intelligence.
SciEval: A Multi-Level Large Language Model Evaluation Benchmark for Scientific Research
This design suffers from data leakage problem and lacks the evaluation of subjective Q/A ability.
LibriSQA: A Novel Dataset and Framework for Spoken Question Answering with Large Language Models
While Large Language Models (LLMs) have demonstrated commendable performance across a myriad of domains and tasks, existing LLMs still exhibit a palpable deficit in handling multimodal functionalities, especially for the Spoken Question Answering (SQA) task which necessitates precise alignment and deep interaction between speech and text features.
Large Language Models Are Semi-Parametric Reinforcement Learning Agents
By equipping the LLM with a long-term experience memory, REMEMBERER is capable of exploiting the experiences from the past episodes even for different task goals, which excels an LLM-based agent with fixed exemplars or equipped with a transient working memory.
Mobile-Env: Building Qualified Evaluation Benchmarks for LLM-GUI Interaction
The Graphical User Interface (GUI) is pivotal for human interaction with the digital world, enabling efficient device control and the completion of complex tasks.
Knowledge-aware Bayesian Co-attention for Multimodal Emotion Recognition
Multimodal emotion recognition is a challenging research area that aims to fuse different modalities to predict human emotion.
Review for AI-based Open-Circuit Faults Diagnosis Methods in Power Electronics Converters
Power electronics converters have been widely used in aerospace system, DC transmission, distributed energy, smart grid and so forth, and the reliability of power electronics converters has been a hotspot in academia and industry.
Multi-level Fusion of Wav2vec 2.0 and BERT for Multimodal Emotion Recognition
The research and applications of multimodal emotion recognition have become increasingly popular recently.
TIE: Topological Information Enhanced Structural Reading Comprehension on Web Pages
Recently, the structural reading comprehension (SRC) task on web pages has attracted increasing research interests.
WebSRC: A Dataset for Web-Based Structural Reading Comprehension
In this paper, we introduce the task of structural reading comprehension (SRC) on web.
An Investigation on Different Underlying Quantization Schemes for Pre-trained Language Models
Recently, pre-trained language models like BERT have shown promising performance on multiple natural language processing tasks.
From Pixel to Patch: Synthesize Context-aware Features for Zero-shot Semantic Segmentation
Thus, we focus on zero-shot semantic segmentation, which aims to segment unseen objects with only category-level semantic representations provided for unseen categories.
Context-aware Feature Generation for Zero-shot Semantic Segmentation
In this paper, we propose a novel context-aware feature generation method for zero-shot segmentation named CaGNet.
Ranked #9 on
Zero-Shot Semantic Segmentation
on PASCAL VOC
