AI Papers of the Week
Every paper worth reading in AI, hand-picked one week at a time.
SAM-Med2D
Adapts the Segment Anything Model (SAM) to 2D medical imaging through large-scale medical fine-tuning.
Vector Search with OpenAI Embeddings
Argues, via empirical analysis, that dedicated vector databases aren't necessarily required for modern AI-stack search applications.
AnomalyGPT
Applies large vision-language models to industrial anomaly detection with synthetic data augmentation.
Code Llama
Meta releases Code Llama, a family of code-specialized LLMs built on top of Llama 2.
Survey on Instruction Tuning for LLMs
A comprehensive survey of instruction tuning covering methodology, dataset construction, and applications.
SeamlessM4T
Meta's SeamlessM4T is a unified multilingual and multimodal machine-translation system that handles five translation tasks in one model.
LLMs for Illicit Purposes
A survey cataloguing threats and vulnerabilities arising from LLM deployment.
LLM-Based Autonomous Agents Survey
A comprehensive survey of LLM-based autonomous agents covering construction and applications.
Prompt2Model
CMU's Prompt2Model automates the path from a natural-language task description to a deployable small special-purpose model.
LegalBench
A collaboratively constructed benchmark for measuring legal reasoning in LLMs.
Language to Rewards for Robotic Skill Synthesis
Google's Language-to-Rewards uses LLMs to define reward parameters for robotic RL.
Humpback (Self-Alignment with Instruction Backtranslation)
Meta's Humpback automatically generates instruction-tuning data by back-translating web text into plausible instructions.
Platypus
Platypus is a family of fine-tuned and merged LLMs that topped the Open LLM Leaderboard in August 2023.
Model Compression for LLMs Survey
A survey of recent model-compression techniques applied specifically to LLMs.
GEARS
Stanford's GEARS predicts cellular responses to genetic perturbation using deep learning + a gene-relationship knowledge graph.
OctoPack
Hugging Face releases OctoPack, a 4TB dataset of Git commits across 350 programming languages for instruction-tuning code LLMs.
Bayesian Flow Networks (BFN)
Introduces a new class of generative models that combine Bayesian inference with deep learning.
D-Bot (LLMs as Database Administrators)
Introduces D-Bot, an LLM-based framework that continuously acquires database-administration knowledge from textual sources.
AgentBench
Tsinghua's AgentBench is a multidimensional benchmark for LLM-as-Agent reasoning and decision-making across 8 environments.
PUG (Photorealistic Unreal Graphics)
Meta's PUG uses Unreal Engine to generate photorealistic, semantically controllable synthetic datasets for vision research.
Trustworthy LLMs
Presents a comprehensive framework of categories for assessing LLM trustworthiness.
Open Problems and Limitations of RLHF
A comprehensive survey of open problems and fundamental limitations of RLHF as an alignment approach.
Med-Flamingo
Stanford's Med-Flamingo is a multimodal medical model supporting in-context learning for few-shot medical visual QA.
ToolLLM
Tsinghua's ToolLLM enables LLMs to interact with 16,000+ real-world APIs through a comprehensive framework for tool-using LLMs.