Trending Research
Data Formulator 2: Iteratively Creating Rich Visualizations with AI
To create rich visualizations, data analysts often need to iterate back and forth among data processing and chart specification to achieve their goals.
LLM4Decompile: Decompiling Binary Code with Large Language Models
Decompilation aims to convert binary code to high-level source code, but traditional tools like Ghidra often produce results that are difficult to read and execute.
Cut Your Losses in Large-Vocabulary Language Models
We implement a custom kernel that performs the matrix multiplications and the log-sum-exp reduction over the vocabulary in flash memory, making global memory consumption for the cross-entropy computation negligible.
Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approach
seal-rg/recurrent-pretraining
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We scale a proof-of-concept model to 3. 5 billion parameters and 800 billion tokens.
Light-A-Video: Training-free Video Relighting via Progressive Light Fusion
Second, leveraging the physical principle of light transport independence, we apply linear blending between the source video's appearance and the relighted appearance, using a Progressive Light Fusion (PLF) strategy to ensure smooth temporal transitions in illumination.
Magic 1-For-1: Generating One Minute Video Clips within One Minute
da-group-pku/magic-1-for-1
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The key idea is simple: factorize the text-to-video generation task into two separate easier tasks for diffusion step distillation, namely text-to-image generation and image-to-video generation.
OmniParser for Pure Vision Based GUI Agent
The recent success of large vision language models shows great potential in driving the agent system operating on user interfaces.
Ranked #10 on
Natural Language Visual Grounding
on ScreenSpot
PIKE-RAG: sPecIalized KnowledgE and Rationale Augmented Generation
Despite notable advancements in Retrieval-Augmented Generation (RAG) systems that expand large language model (LLM) capabilities through external retrieval, these systems often struggle to meet the complex and diverse needs of real-world industrial applications.
Agentic Reasoning: Reasoning LLMs with Tools for the Deep Research
We introduce Agentic Reasoning, a framework that enhances large language model (LLM) reasoning by integrating external tool-using agents.
Flaming-hot Initiation with Regular Execution Sampling for Large Language Models
volcengine/verl
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Since the release of ChatGPT, large language models (LLMs) have demonstrated remarkable capabilities across various domains.
