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Found 39 papers, 16 papers with code
YuE: Scaling Open Foundation Models for Long-Form Music Generation
We tackle the task of long-form music generation--particularly the challenging \textbf{lyrics-to-song} problem--by introducing YuE, a family of open foundation models based on the LLaMA2 architecture.
Semantic Web and Creative AI -- A Technical Report from ISWS 2023
ISWS 2023 explored various intersections between Semantic Web technologies and creative AI.
A Machine Learning Approach for Emergency Detection in Medical Scenarios Using Large Language Models
The results demonstrate exceptional performance, with the LLaMA 2 (7B) model achieving 99. 7% accuracy and the LLaMA 3. 2 (3B) model reaching 99. 6% accuracy with optimal prompt engineering.
Entire-Space Variational Information Exploitation for Post-Click Conversion Rate Prediction
Sample selection bias (SSB) and data sparsity (DS) are two persistent challenges for post-click conversion rate (CVR) estimation.
Volatility-Volume Order Slicing via Statistical Analysis
This paper addresses the challenges faced in large-volume trading, where executing substantial orders can result in significant market impact and slippage.
InternLM-XComposer2.5-OmniLive: A Comprehensive Multimodal System for Long-term Streaming Video and Audio Interactions
Recent advancements in multimodal large language models (MLLMs) have made significant strides in open-world understanding.
Simulator HC: Regression-based Online Simulation of Starting Problem-Solution Pairs for Homotopy Continuation in Geometric Vision
While automatically generated polynomial elimination templates have sparked great progress in the field of 3D computer vision, there remain many problems for which the degree of the constraints or the number of unknowns leads to intractability.
Mobility-LLM: Learning Visiting Intentions and Travel Preferences from Human Mobility Data with Large Language Models
Drawing inspiration from the exceptional semantic understanding and contextual information processing capabilities of large language models (LLMs) across various domains, we present Mobility-LLM, a novel framework that leverages LLMs to analyze check-in sequences for multiple tasks.
The Influence of Initial Connectivity on Biologically Plausible Learning
Understanding how the brain learns can be advanced by investigating biologically plausible learning rules -- those that obey known biological constraints, such as locality, to serve as valid brain learning models.
fCOP: Focal Length Estimation from Category-level Object Priors
In the realm of computer vision, the perception and reconstruction of the 3D world through vision signals heavily rely on camera intrinsic parameters, which have long been a subject of intense research within the community.
OmniBench: Towards The Future of Universal Omni-Language Models
Recent advancements in multimodal large language models (MLLMs) have focused on integrating multiple modalities, yet their ability to simultaneously process and reason across different inputs remains underexplored.
Can LLMs "Reason" in Music? An Evaluation of LLMs' Capability of Music Understanding and Generation
Yet scant research explores the details of how these LLMs perform on advanced music understanding and conditioned generation, especially from the multi-step reasoning perspective, which is a critical aspect in the conditioned, editable, and interactive human-computer co-creation process.
InternLM-XComposer-2.5: A Versatile Large Vision Language Model Supporting Long-Contextual Input and Output
This long-context capability allows IXC-2. 5 to excel in tasks requiring extensive input and output contexts.
Ranked #10 on
Video Question Answering
on TVBench
MAP-Neo: Highly Capable and Transparent Bilingual Large Language Model Series
To improve the transparency of LLMs, the research community has formed to open-source truly open LLMs (e. g., Pythia, Amber, OLMo), where more details (e. g., pre-training corpus and training code) are being provided.
InternLM-XComposer2-4KHD: A Pioneering Large Vision-Language Model Handling Resolutions from 336 Pixels to 4K HD
The Large Vision-Language Model (LVLM) field has seen significant advancements, yet its progression has been hindered by challenges in comprehending fine-grained visual content due to limited resolution.
Ranked #47 on
Visual Question Answering
on MM-Vet
InternLM2 Technical Report
The evolution of Large Language Models (LLMs) like ChatGPT and GPT-4 has sparked discussions on the advent of Artificial General Intelligence (AGI).
Ranked #5 on
Long-Context Understanding
on Ada-LEval (BestAnswer)
Driving Style Alignment for LLM-powered Driver Agent
Recently, LLM-powered driver agents have demonstrated considerable potential in the field of autonomous driving, showcasing human-like reasoning and decision-making abilities. However, current research on aligning driver agent behaviors with human driving styles remains limited, partly due to the scarcity of high-quality natural language data from human driving behaviors. To address this research gap, we propose a multi-alignment framework designed to align driver agents with human driving styles through demonstrations and feedback.
InternLM-XComposer2: Mastering Free-form Text-Image Composition and Comprehension in Vision-Language Large Model
We introduce InternLM-XComposer2, a cutting-edge vision-language model excelling in free-form text-image composition and comprehension.
Ranked #18 on
Visual Question Answering
on MM-Vet v2
Audiobox: Unified Audio Generation with Natural Language Prompts
Research communities have made great progress over the past year advancing the performance of large scale audio generative models for a single modality (speech, sound, or music) through adopting more powerful generative models and scaling data.
Ranked #1 on
Audio Generation
on AudioCaps
(FAD metric)
Harnessing Inherent Noises for Privacy Preservation in Quantum Machine Learning
Quantum computing revolutionizes the way of solving complex problems and handling vast datasets, which shows great potential to accelerate the machine learning process.
Optimised Storage for Datalog Reasoning
Materialisation facilitates Datalog reasoning by precomputing all consequences of the facts and the rules so that queries can be directly answered over the materialised facts.
InternLM-XComposer: A Vision-Language Large Model for Advanced Text-image Comprehension and Composition
We propose InternLM-XComposer, a vision-language large model that enables advanced image-text comprehension and composition.
Ranked #9 on
Visual Question Answering (VQA)
on InfiMM-Eval
Ultrafast-and-Ultralight ConvNet-Based Intelligent Monitoring System for Diagnosing Early-Stage Mpox Anytime and Anywhere
Due to the absence of more efficient diagnostic tools, the spread of mpox continues to be unchecked.
Enhancing Datalog Reasoning with Hypertree Decompositions
In this paper, we provide algorithms that exploit hypertree decompositions for the materialisation and incremental evaluation of Datalog programs.
Accelerating Globally Optimal Consensus Maximization in Geometric Vision
Branch-and-bound-based consensus maximization stands out due to its important ability of retrieving the globally optimal solution to outlier-affected geometric problems.
Mpox-AISM: AI-Mediated Super Monitoring for Mpox and Like-Mpox
Swift and accurate diagnosis for earlier-stage monkeypox (mpox) patients is crucial to avoiding its spread.
Data-based Polymer-Unit Fingerprint (PUFp): A Newly Accessible Expression of Polymer Organic Semiconductors for Machine Learning
By investigating the combinations of polymer units with mobility performance, a scheme for designing polymer OSC materials by combining ML approaches and PUFp information is proposed to not only passively predict OSC mobility but also actively provide structural guidance for new high-mobility OSC material design.
CheXplaining in Style: Counterfactual Explanations for Chest X-rays using StyleGAN
Deep learning models used in medical image analysis are prone to raising reliability concerns due to their black-box nature.
Two New Stenosis Detection Methods of Coronary Angiograms
Two vascular stenosis detection methods are proposed to assist the diagnosis.
Boosting RANSAC via Dual Principal Component Pursuit
In this paper, we revisit the problem of local optimization in RANSAC.
Open Set Domain Adaptation with Zero-shot Learning on Graph
Thus the classification ability of the source domain is transferred to the target domain and the model can distinguish the unknown classes with prior knowledge.
Two New Stenosis Detection Methods of Coronary Angiograms
Two vascular stenosis detection methods are proposed to assist the diagnosis.
Diverse Melody Generation from Chinese Lyrics via Mutual Information Maximization
In this paper, we propose to adapt the method of mutual information maximization into the task of Chinese lyrics conditioned melody generation to improve the generation quality and diversity.
Evaluation of Inference Attack Models for Deep Learning on Medical Data
This paper aims to attract interest from researchers in the medical deep learning community to this important problem.
Revealing Secrets in SPARQL Session Level
Based on Semantic Web technologies, knowledge graphs help users to discover information of interest by using live SPARQL services.
Differentially Private and Fair Classification via Calibrated Functional Mechanism
In order to enforce $\epsilon$-differential privacy and fairness, we leverage the functional mechanism to add different amounts of Laplace noise regarding different attributes to the polynomial coefficients of the objective function in consideration of fairness constraint.
From Dark Matter to Galaxies with Convolutional Neural Networks
Cosmological simulations play an important role in the interpretation of astronomical data, in particular in comparing observed data to our theoretical expectations.
From Dark Matter to Galaxies with Convolutional Networks
In combination with current and upcoming data from cosmological observations, our method has the potential to answer fundamental questions about our Universe with the highest accuracy.
Image Registration Based Flicker Solving in Video Face Replacement and Analysis Based Sub-pixel Image Registration
In this paper, a framework of video face replacement is proposed and it deals with the flicker of swapped face in video sequence.
