??Top ML Papers of the Week

The top ML Papers of the Week (May 8 - May 14):

1). LLM explains neurons in LLMs?- applies GPT-4 to automatically write explanations on the behavior of neurons in LLMs and even score those explanations; this offers a promising way to improve interpretability in future LLMs and potentially detect alignment and safety problems. (paper ?|?tweet )

2). PaLM 2?- a new state-of-the-art language model integrated into AI features and tools like Bard and the PaLM API; displays competitive performance in mathematical reasoning compared to GPT-4; instruction-tuned model, Flan-PaLM 2, shows good performance on benchmarks like MMLU and BIG-bench Hard. (paper ?|?tweet )

3). ImageBind?- an approach that learns joint embedding data across six modalities at once; extends zero-shot capabilities to new modalities and enables emergent applications including cross-modal retrieval, composing modalities with arithmetic, cross-modal detection, and generation. (paper ?|?tweet )

4). TidyBot?- shows that robots can combine language-based planning and perception with the few-shot summarization capabilities of LLMs to infer generalized user preferences that are applicable to future interactions. (paper ?|?tweet )

5). Unfaithful Explanations in Chain-of-Thought Prompting -?demonstrates that CoT explanations can misrepresent the true reason for a model’s prediction; when models are biased towards incorrect answers, CoT generation explanations supporting those answers. (paper ?|?tweet )

6). InstructBLIP?- explores visual-language instruction tuning based on the pre-trained BLIP-2 models; achieves state-of-the-art zero-shot performance on 13 held-out datasets, outperforming BLIP-2 and Flamingo. (paper ?|?tweet )

7). Active Retrieval Augmented LLMs?- introduces FLARE, retrieval augmented generation to improve the reliability of LLMs; FLARE actively decides when and what to retrieve across the course of the generation; demonstrates superior or competitive performance on long-form knowledge-intensive generation tasks. (paper ?|?tweet )

8). FrugalGPT -?presents strategies to reduce the inference cost associated with using LLMs while improving performance. (paper ?|?tweet )

9). StarCoder?- an open-access 15.5B parameter LLM with 8K context length and is trained on large amounts of code spanning 80+ programming languages. (paper ?|?tweet )

10). MultiModal-GPT?- a vision and language model for multi-round dialogue with humans; the model is fine-tuned from OpenFlamingo, with LoRA added in the cross-attention and self-attention parts of the language model. (paper ?|?tweet )