Collections

1

Video Creation by Demonstration

Paper • 2412.09551 • Published Dec 12, 2024 • 8
DiffSensei: Bridging Multi-Modal LLMs and Diffusion Models for Customized Manga Generation

Paper • 2412.07589 • Published Dec 10, 2024 • 45
Unraveling the Complexity of Memory in RL Agents: an Approach for Classification and Evaluation

Paper • 2412.06531 • Published Dec 9, 2024 • 71
APOLLO: SGD-like Memory, AdamW-level Performance

Paper • 2412.05270 • Published Dec 6, 2024 • 38

34

Can Large Language Models Understand Context?

Paper • 2402.00858 • Published Feb 1, 2024 • 22
OLMo: Accelerating the Science of Language Models

Paper • 2402.00838 • Published Feb 1, 2024 • 82
Self-Rewarding Language Models

Paper • 2401.10020 • Published Jan 18, 2024 • 146
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity

Paper • 2401.17072 • Published Jan 30, 2024 • 25

Video Creation by Demonstration

DiffSensei: Bridging Multi-Modal LLMs and Diffusion Models for Customized Manga Generation

Unraveling the Complexity of Memory in RL Agents: an Approach for Classification and Evaluation

APOLLO: SGD-like Memory, AdamW-level Performance

Can Large Language Models Understand Context?

OLMo: Accelerating the Science of Language Models

Self-Rewarding Language Models

SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity

Mulberry: Empowering MLLM with o1-like Reasoning and Reflection via Collective Monte Carlo Tree Search

Token-Budget-Aware LLM Reasoning

Efficiently Serving LLM Reasoning Programs with Certaindex

B-STaR: Monitoring and Balancing Exploration and Exploitation in Self-Taught Reasoners

RobustFT: Robust Supervised Fine-tuning for Large Language Models under Noisy Response

B-STaR: Monitoring and Balancing Exploration and Exploitation in Self-Taught Reasoners

OpenAI o1 System Card

Revisiting In-Context Learning with Long Context Language Models

Flowing from Words to Pixels: A Framework for Cross-Modality Evolution

No More Adam: Learning Rate Scaling at Initialization is All You Need

Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference

Autoregressive Video Generation without Vector Quantization

Beyond Examples: High-level Automated Reasoning Paradigm in In-Context Learning via MCTS

o1-Coder: an o1 Replication for Coding

A Simple and Provable Scaling Law for the Test-Time Compute of Large Language Models

Reverse Thinking Makes LLMs Stronger Reasoners

Qwen2.5 Technical Report

SPaR: Self-Play with Tree-Search Refinement to Improve Instruction-Following in Large Language Models

Scaling test-time compute

Reverse Thinking Makes LLMs Stronger Reasoners

Large Language Models Can Self-Improve in Long-context Reasoning

Reverse Thinking Makes LLMs Stronger Reasoners

Training Large Language Models to Reason in a Continuous Latent Space

Rethinking Data Selection at Scale: Random Selection is Almost All You Need

From Generalist to Specialist: Adapting Vision Language Models via Task-Specific Visual Instruction Tuning

Emergent properties with repeated examples

Personalized Visual Instruction Tuning

Revisit Large-Scale Image-Caption Data in Pre-training Multimodal Foundation Models

From Code to Correctness: Closing the Last Mile of Code Generation with Hierarchical Debugging

Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Multimodal Models

EuroLLM: Multilingual Language Models for Europe