OPENSCHOLAR: SYNTHESIZING SCIENTIFICLITERATURE WITH RETRIEVAL-AUGMENTED LMS | #ai #genai #llm #2024
AI Today27 Nov 2024

OPENSCHOLAR: SYNTHESIZING SCIENTIFICLITERATURE WITH RETRIEVAL-AUGMENTED LMS | #ai #genai #llm #2024

Paper: https://arxiv.org/pdf/2411.14199 Github: https://github.com/AkariAsai/OpenScholar The research introduces OpenScholar, a retrieval-augmented large language model (LLM) designed for synthesizing scientific literature. OpenScholar uses a large datastore of open-access papers and iterative self-feedback to generate high-quality responses to scientific questions, including accurate citations. A new benchmark, ScholarQABench, is introduced for evaluating open-ended scientific question answering, incorporating both automatic and human evaluations. Experiments demonstrate OpenScholar's superior performance compared to other LLMs and even human experts in certain aspects, particularly in terms of information coverage. Limitations of OpenScholar and ScholarQABench are discussed, alongside plans for open-sourcing the model and benchmark. ai , llm , retrieval augmented, rag , artificial intelligence , arxiv , research , paper , publication , genai , generativeai, agentic

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OpenAI's o3 and o3-mini: A New Frontier in AI | #ai #2024 #genai

OpenAI's o3 and o3-mini: A New Frontier in AI | #ai #2024 #genai

Blog: https://openai.com/12-days/ OpenAI announced two new large language models, o3 and o3-mini, showcasing significantly improved performance on various benchmarks, including coding, mathematics, ...

21 Dec 202422min

Alignment Faking in Large Language Models | #ai #2024 #genai

Alignment Faking in Large Language Models | #ai #2024 #genai

Paper: https://arxiv.org/pdf/2412.14093 This research paper explores "alignment faking" in large language models (LLMs). The authors designed experiments to provoke LLMs into concealing their true pr...

21 Dec 202414min

Veo 2, Imagen 3, and Whisk: State-of-the-Art AI Image and Video Generation | #ai #2024 #genai

Veo 2, Imagen 3, and Whisk: State-of-the-Art AI Image and Video Generation | #ai #2024 #genai

Blog: https://blog.google/technology/google... Google announced updates to its AI video and image generation models, Veo 2 and Imagen 3, boasting state-of-the-art capabilities in realism and style d...

21 Dec 202419min

Allegro: Open the Black Box of Commercial-Level Video Generation Model | #ai #2024 #genai

Allegro: Open the Black Box of Commercial-Level Video Generation Model | #ai #2024 #genai

Paper: https://arxiv.org/pdf/2411.01747 This research report introduces Allegro, a novel, open-source text-to-video generation model that surpasses existing open-source and many commercial models in ...

4 Dec 202419min

DynaSaur : Large Language Agents Beyond Predefined Actions | #ai #2024 #genai

DynaSaur : Large Language Agents Beyond Predefined Actions | #ai #2024 #genai

Paper: https://arxiv.org/pdf/2411.01747 The paper "DynaSaur: Large Language Agents Beyond Predefined Actions" introduces a novel large language model (LLM) agent framework that dynamically generates ...

4 Dec 202419min

STAR ATTENTION: EFFICIENT LLM INFERENCE OVER LONG SEQUENCES | #ai #2024 #genai

STAR ATTENTION: EFFICIENT LLM INFERENCE OVER LONG SEQUENCES | #ai #2024 #genai

Paper: https://arxiv.org/pdf/2411.17116 The paper introduces Star Attention, a novel two-phase attention mechanism for efficient Large Language Model (LLM) inference on long sequences. It improves co...

4 Dec 202416min

FERRET-UI 2: MASTERING UNIVERSAL USER INTERFACE UNDERSTANDING ACROSS PLATFORMS | #ai #2024 #genai

FERRET-UI 2: MASTERING UNIVERSAL USER INTERFACE UNDERSTANDING ACROSS PLATFORMS | #ai #2024 #genai

Paper: https://arxiv.org/pdf/2410.18967 The paper introduces Ferret-UI 2, a multimodal large language model (MLLM) that significantly improves upon its predecessor, Ferret-UI, by enabling universal u...

27 Nov 202414min

Adapting While Learning: Grounding LLMs for Scientific Problems I-Tool Usage Adaptation | #ai #2024

Adapting While Learning: Grounding LLMs for Scientific Problems I-Tool Usage Adaptation | #ai #2024

Paper: https://arxiv.org/abs/2411.00412 This research introduces a novel two-stage training method to improve Large Language Models' (LLMs) ability to solve complex scientific problems. The method, c...

27 Nov 202414min

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