Trending Research
MonkeyOCR: Document Parsing with a Structure-Recognition-Relation Triplet Paradigm
We introduce MonkeyOCR, a vision-language model for document parsing that advances the state of the art by leveraging a Structure-Recognition-Relation (SRR) triplet paradigm.
Practical Efficiency of Muon for Pretraining
We demonstrate that Muon, the simplest instantiation of a second-order optimizer, explicitly expands the Pareto frontier over AdamW on the compute-time tradeoff.
Audio Flamingo: A Novel Audio Language Model with Few-Shot Learning and Dialogue Abilities
Augmenting large language models (LLMs) to understand audio -- including non-speech sounds and non-verbal speech -- is critically important for diverse real-world applications of LLMs.
Ranked #1 on
Retrieval-augmented Few-shot In-context Audio Captioning
on AudioCaps
(using extra training data)
TCSinger 2: Customizable Multilingual Zero-shot Singing Voice Synthesis
To overcome these challenges, we introduce TCSinger 2, a multi-task multilingual zero-shot SVS model with style transfer and style control based on various prompts.
TradingAgents: Multi-Agents LLM Financial Trading Framework
Significant progress has been made in automated problem-solving using societies of agents powered by large language models (LLMs).
ThinkSound: Chain-of-Thought Reasoning in Multimodal Large Language Models for Audio Generation and Editing
While end-to-end video-to-audio generation has greatly improved, producing high-fidelity audio that authentically captures the nuances of visual content remains challenging.
SepLLM: Accelerate Large Language Models by Compressing One Segment into One Separator
HKUDS/SepLLM
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This observation suggests that information of the segments between these separator tokens can be effectively condensed into the separator tokens themselves without significant information loss.
R1-Reward: Training Multimodal Reward Model Through Stable Reinforcement Learning
Our reward model, R1-Reward, trained using the StableReinforce algorithm on this dataset, significantly improves performance on multimodal reward modeling benchmarks.
DiC: Rethinking Conv3x3 Designs in Diffusion Models
Diffusion models have shown exceptional performance in visual generation tasks.
Set You Straight: Auto-Steering Denoising Trajectories to Sidestep Unwanted Concepts
lileyang1210/ant
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Anchor-free methods risk disrupting sampling trajectories, leading to visual artifacts, while anchor-based methods rely on the heuristic selection of anchor concepts.
