Papers

Awesome Loop Models is a curated, interactively browsable list of papers and long-form technical posts about loop models, architectures that reuse a shared learned layer or block within a single forward pass.

• Papers

A curated, actively updated archive of research paper reviews toward artificial general intelligence, organized around agents, architecture, training, evaluation, RAG and knowledge, and on-device AI.

• Papers

A NeurIPS 2026 paper and reference implementation showing that standard vision-language models can be trained to do object-level 3D understanding, depth estimation, pixel correspondence and camera pose estimation without special architectures or losses.

• Models
• Papers

A searchable, filterable gallery of well-designed Figure 1 and teaser images from top machine-learning conference papers between 2023 and 2026, meant as visual reference for designing a paper's own opening figure.

• Design tools
• Papers

A research project that has an AI agent discover executable code representations of the physical world from video, so a vision-language model can verify and reuse explicit states, dynamics and mechanisms instead of only matching pixels.

• Papers

A three-stage diffusion-based framework, from Tencent ARC, for automatically colorizing black-and-white image sequences, such as cartoon or comic panels, while keeping the same character and object identity across frames.

• Generative media
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A survey repository accompanying a paper on how large language model benchmarking has moved from static test sets, which risk data contamination from training corpora, to dynamic evaluation methods designed to avoid it.

• AI evals
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A list of recent developments in retrieval-augmented generation for large language models, tracking accepted papers by conference and year along with common evaluation datasets.

• RAG
• Curated lists
• Papers

A paper collection accompanying a survey on AI-assisted and automated scientific research, organized around the full research lifecycle from idea generation through writing, peer review and dissemination.

• Curated lists
• Papers

A retrieval-augmented generation system that builds a hierarchical knowledge index over a document corpus, described in an EMNLP 2025 Findings paper.

• RAG
• Papers

A curated collection of papers and resources on on-policy distillation for large language models, accompanying a survey paper and a companion site with full-text search.

• Curated lists
• Papers

A curated collection of papers, summaries and code on deep neural network compression, covering quantization, pruning and distillation.

• Curated lists
• Papers

Research code from Meta that jointly pretrains a retrieval-augmented sequence-to-sequence language model, combining a dense passage retriever with an encoder-decoder model for few-shot question answering and other tasks.

• RAG
• Papers

CodeRL is the official research code for a NeurIPS 2022 paper that trains a pretrained code-generation language model with deep reinforcement learning, using a critic network to judge functional correctness and guide a regeneration step at inference time.

• Models
• Papers

A curated list of research papers and code for diffusion-model inference, covering sampling, caching, quantization, parallelism, and attention optimizations for image and video diffusion transformers.

• Curated lists
• Papers

A curated, actively updated list of papers, surveys, frameworks and posts about machine unlearning in large language models, that is, removing specific knowledge or training data from a model after the fact.

• Papers

Awesome Scientific Language Models is a curated list of pre-trained language models for scientific domains such as mathematics, physics, chemistry, materials science, biology, medicine and geoscience, accompanying a survey paper on scientific large language models.

• Papers

Awesome Adaptation of Agentic AI is a curated list of research papers on adaptation strategies for agentic AI systems, accompanying the paper Adaptation of Agentic AI.

• Papers

A survey and continuously updated collection of vision-language model papers and models, tracking the architectural evolution of VLMs across eras from contrastive alignment to unified multimodal transformers.

• Papers

A curated, continuously updated reading list about OCR in the era of large language models, tracking research from the past five years on document parsing, document understanding and text-rich visual understanding.

• Papers

An academic survey and paper collection on aligning large language models with human expectations, covering data collection, training methodologies and evaluation for alignment research.

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An actively maintained collection of research papers on building autonomous agents, organized separately for reinforcement-learning-based agents and large-language-model-based agents.

• Papers

A personal, actively updated reading list of research papers on multimodal and large language models, organized into dozens of topic sections from alignment and reasoning to hallucination and world models.

• Papers

Research code accompanying a paper on masked diffusion language models for code generation, including inference examples and a Coupled-GRPO post-training method.

• Models
• Papers