# Oct 21, 2024

## Daily

### Janus: Decoupling Visual Encoding for Multimodal Understanding and Generation

**Janus** is an innovative **autoregressive framework** that enhances multimodal understanding by decoupling visual encoding, allowing for improved flexibility and performance compared to traditional models.

### 3D-Printed Active Electronics

MIT researchers have developed **semiconductor-free logic gates** using 3D printing, enabling the potential for **widespread electronics fabrication** without traditional semiconductor facilities.

### [R] Google Shopping 10M dataset for large scale multimodal product retrieval and ranking

The **Marqo Google Shopping 10M dataset** is now available on Hugging Face, featuring **10 million rows** of data, including queries, product titles, images, and relevance ranks, making it a premier resource for **multimodal product retrieval** research.

### All-optical switch device paves way for faster fiber-optic communication

**An ultrafast all-optical switch** developed by a University of Michigan team utilizes **circularly polarized light** to control light signals without electrical conversion, enhancing speed and energy efficiency in fiber-optic communication.

### [R] RWKV-7: attention-free and surpassing strong Modded-GPT baseline (the one with Muon optimizer), while only using headsz 64

**RWKV-7**, an entirely **RNN-based** model, has demonstrated the ability to **surpass** the strong Modded-GPT baseline, achieving a loss of **3.26xx** with potential for further optimization.

### [D] Last Week in Medical AI: Top LLM Research Papers/Models (October 12 - October 19)

**MedLFQA** introduces a benchmark dataset for evaluating the **factuality** of long-form answers from **medical LLMs**, enhancing the reliability of AI-generated medical information.

### Enhancing Large Language Models' Situated Faithfulness to External Contexts

**Situated faithfulness** in Large Language Models (LLMs) is crucial, as it allows them to dynamically assess the reliability of external information against their internal knowledge, addressing the issue of **inaccurate or misleading contexts**.

### 🤗Llama 3.2 in Keras

**Llama 3.2 is fully operational in Keras**, allowing users to load models directly from Hugging Face checkpoints with seamless conversion, enhancing accessibility for developers.

### Large Language Models Are Overparameterized Text Encoders

**Pruning the last $p%$ layers** of large language models (LLMs) before supervised training can significantly reduce **memory and inference time** while maintaining performance, with up to **30% layers pruned** with negligible impact and **80% with modest drop**.

### LoGU: Long-form Generation with Uncertainty Expressions

The **LoGU** framework addresses the challenge of **long-form generation** in Large Language Models (LLMs) by enabling them to express **uncertainty**, thus reducing the incidence of **hallucinations** in generated content.