Trending Research
Branch-Train-MiX: Mixing Expert LLMs into a Mixture-of-Experts LLM
Leeroo-AI/mergoo
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We investigate efficient methods for training Large Language Models (LLMs) to possess capabilities in multiple specialized domains, such as coding, math reasoning and world knowledge.
Ranked #30 on
Question Answering
on TriviaQA
StreamingT2V: Consistent, Dynamic, and Extendable Long Video Generation from Text
picsart-ai-research/streamingt2v
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To overcome these limitations, we introduce StreamingT2V, an autoregressive approach for long video generation of 80, 240, 600, 1200 or more frames with smooth transitions.
AutoCodeRover: Autonomous Program Improvement
Recent progress in Large Language Models (LLMs) has significantly impacted the development process, where developers can use LLM-based programming assistants to achieve automated coding.
SoccerNet Game State Reconstruction: End-to-End Athlete Tracking and Identification on a Minimap
This tracking and identification process is crucial for reconstructing the game state, defined by the athletes' positions and identities on a 2D top-view of the pitch, (i. e. a minimap).
InstantStyle: Free Lunch towards Style-Preserving in Text-to-Image Generation
Tuning-free diffusion-based models have demonstrated significant potential in the realm of image personalization and customization.
Attention Satisfies: A Constraint-Satisfaction Lens on Factual Errors of Language Models
microsoft/mechanistic-error-probe
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We investigate the internal behavior of Transformer-based Large Language Models (LLMs) when they generate factually incorrect text.
OneChart: Purify the Chart Structural Extraction via One Auxiliary Token
To address this, we propose OneChart: a reliable agent specifically devised for the structural extraction of chart information.
Robust Speech Recognition via Large-Scale Weak Supervision
We study the capabilities of speech processing systems trained simply to predict large amounts of transcripts of audio on the internet.
Ranked #1 on
Speech Recognition
on Common Voice Italian
(using extra training data)
ChangeMamba: Remote Sensing Change Detection with Spatio-Temporal State Space Model
For the change decoder, which is available in all three architectures, we propose three spatio-temporal relationship modeling mechanisms, which can be naturally combined with the Mamba architecture and fully utilize its attribute to achieve spatio-temporal interaction of multi-temporal features, thereby obtaining accurate change information.
Ranked #1 on
2D Semantic Segmentation
on xBD
TSMixer: Lightweight MLP-Mixer Model for Multivariate Time Series Forecasting
TSMixer outperforms state-of-the-art MLP and Transformer models in forecasting by a considerable margin of 8-60%.
Multivariate Time Series Forecasting
Representation Learning
+2
