2/ Fact-checking with LLMs – investigates fact-checking capabilities of LLMs; shows the enhanced prowess of LLMs when equipped with contextual information; GPT4 outperforms GPT-3, but accuracy varies based on query language & claim veracity.
@dair_ai
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Top ML Papers: Ring Attention, LLMs Rules Learning, Healthcare
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Top ML Papers of the Week (Oct 9 – Oct 15): – Instruct-Retro
– Ring Attention
– LLMs can Learn Rules
– A Survey of LLMs for Healthcare
– Meta Chain-of-Thought Prompting
– Toward Language Agent Fine-tuning
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1/ Ring Attention – a memory-efficient approach that leverages -
LLMs Generate Synthetic Datasets Solving Data Labeling
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Harnessing LLMs to Generate Synthetic Datasets In the context of machine learning, there's often a lack of labeled data or very little of it. This data collection and labeling process typically ends up taking a lot of effort and time. With the advent of LLMs, the paradigm
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Top ML Papers: LLMs, Streaming, and Multimodal Advances
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Top ML Papers of the Week (Oct 2 – Oct 8): – StreamingLLM – Analogical Prompting
– The Dawn of LMMs
– Neural Developmental Programs
– LLMs Represent Space and Time
– Retrieval meets Long Context LLMs
… —- 1/ LLMs Represent Space and Time – discovers that LLMs learn linear -
PaLM 2 Excels in Multilingual QA and Mathematical Reasoning
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Curious about the capabilities of PaLM 2? In our new paper explainer, we summarize the main contributions of PaLM 2, a model that excels in various tasks like multilingual question answering and arithmetic reasoning. PaLM 2 mathematical reasoning performance surpasses SoTA (at
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MentalLlaMa: Open-Source LLM for Mental Health Analysis
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9/ MentalLlaMa – an open-source LLM series for interpretable mental health analysis with instruction-following capability; proposes a multi-task and multi-source interpretable mental health instruction dataset on social media with 105K data samples.
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Logical Chain-of-Thought Framework Improves LLM Reasoning
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10/ Logical Chain-of-Thought in LLMs – a new neurosymbolic framework to improve zero-shot chain-of-thought reasoning in LLMs; leverages principles from symbolic logic to verify and revise reasoning processes to improve the reasoning capabilities of LLMs.
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Qwen LLM Demonstrates RLHF Strength in Tool Use and Planning
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8/ Qwen LLM – proposes a series of LLMs demonstrating the strength of RLHF on tasks involving tool use and planning capabilities for creating language agents.
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LlaVA-RLHF Achieves GPT-4 Level Performance on Multimodal Tasks
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6/ LlaVA-RLHF – adapts factually augmented RLHF to aligning large multimodal models; this approach alleviates the reward hacking in RLHF and improves performance on the LlaVA-Bench dataset with the 94% performance level of the text-only GPT-4.
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LLM Alignment Survey: Comprehensive Review of Safety and Interpretability
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7/ LLM Alignment Survey – a comprehensive survey paper on LLM alignment; topics include Outer Alignment, Inner Alignment, Mechanistic Interpretability, Attacks on Aligned LLMs, Alignment Evaluation, Future Directions, and Discussions.