Trending Research
How to Train Long-Context Language Models (Effectively)
We study continued training and supervised fine-tuning (SFT) of a language model (LM) to make effective use of long-context information.
RouteLLM: Learning to Route LLMs with Preference Data
lm-sys/routellm
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Large language models (LLMs) exhibit impressive capabilities across a wide range of tasks, yet the choice of which model to use often involves a trade-off between performance and cost.
Diffusion Models are Evolutionary Algorithms
Zhangyanbo/diffusion-evolution
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In a convergence of machine learning and biology, we reveal that diffusion models are evolutionary algorithms.
PhysGen: Rigid-Body Physics-Grounded Image-to-Video Generation
We present PhysGen, a novel image-to-video generation method that converts a single image and an input condition (e. g., force and torque applied to an object in the image) to produce a realistic, physically plausible, and temporally consistent video.
Generative Agents: Interactive Simulacra of Human Behavior
Believable proxies of human behavior can empower interactive applications ranging from immersive environments to rehearsal spaces for interpersonal communication to prototyping tools.
From Code to Correctness: Closing the Last Mile of Code Generation with Hierarchical Debugging
While large language models have made significant strides in code generation, the pass rate of the generated code is bottlenecked on subtle errors, often requiring human intervention to pass tests, especially for complex problems.
Ranked #3 on
Code Generation
on HumanEval
Generative agent-based modeling with actions grounded in physical, social, or digital space using Concordia
Agent-based modeling has been around for decades, and applied widely across the social and natural sciences.
Resolving Multi-Condition Confusion for Finetuning-Free Personalized Image Generation
Personalized text-to-image generation methods can generate customized images based on the reference images, which have garnered wide research interest.
CtrlA: Adaptive Retrieval-Augmented Generation via Inherent Control
Retrieval-augmented generation (RAG) has emerged as a promising solution for mitigating hallucinations of large language models (LLMs) with retrieved external knowledge.
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.
