Marktechpost

OCTOBER 15, 2024

The key innovation in PAVs is using a “prover policy,” distinct from the base policy that the LLM is following. This enables the LLM to explore a wider range of potential solutions, even when early steps do not immediately lead to a correct solution. Check out the Paper. Don’t Forget to join our 50k+ ML SubReddit.

Machine Learning 119

Machine Learning LLM AI Research AI Researcher 119

Marktechpost

OCTOBER 16, 2024

Specifically, while LLMs are becoming capable of handling longer input sequences, the increase in retrieved information can overwhelm the system. The challenge lies in making sure that the additional context improves the accuracy of the LLM’s outputs rather than confusing the model with irrelevant information.

LLM 111

LLM AI Research AI Researcher Inference Engine 111

Marktechpost

OCTOBER 15, 2024

The key problem, therefore, is how to effectively compress LLM weights without sacrificing accuracy or requiring calibration data. Researchers from Apple and Meta AI introduce SeedLM, a novel approach that aims to overcome the challenges associated with the deployment of large-scale LLMs by providing a data-free compression method.

LLM 111

LLM Inference Engine Natural Language Processing Large Language Models 111

Marktechpost

OCTOBER 18, 2024

Large language models (LLMs) have demonstrated significant reasoning capabilities, yet they face issues like hallucinations and the inability to conduct faithful reasoning. GCR introduces a trie-based index named KG-Trie to integrate KG structures directly into the LLM decoding process. Don’t Forget to join our 50k+ ML SubReddit.

LLM 115

LLM Inference Engine Large Language Models AI 115

Marktechpost

OCTOBER 15, 2024

These workflows are modeled as graphs where nodes represent LLM-invoking actions, and edges represent the dependencies between these actions. The key to AFlow’s efficiency lies in its use of nodes and edges to represent workflows, allowing it to model complex relationships between LLM actions.

Artificial Intelligence 126

Artificial Intelligence Artificial Intelligence Automation Inference Engine 126

Marktechpost

OCTOBER 17, 2024

Katanemo’s Arch-Function transforms workflow automation by simplifying LLM deployment and reducing engineering overhead, making it accessible even for smaller enterprises. Arch-Function is optimized for speed and precision, completing tasks in minutes that previously took hours while effectively adapting to dynamic requirements.

Large Language Models 111

Large Language Models Inference Engine Automation Data Scientist 111

Marktechpost

OCTOBER 27, 2024

LLMs prefer contextual knowledge over their parametric knowledge, but during conflicts, existing solutions that need additional model interactions result in high latency times, making them impractical for real-world applications. Representation engineering emerged as a higher-level framework for understanding LLM behavior at scale.

Large Language Models 119

Large Language Models LLM Inference Engine ML 119

Marktechpost

OCTOBER 26, 2024

Large Language Models (LLMs) have shown remarkable potential in solving complex real-world problems, from function calls to embodied planning and code generation. Researchers from Zhejiang University and Alibaba Group have proposed WORFBENCH, a benchmark for evaluating workflow generation capabilities in LLM agents.

Large Language Models 115

Large Language Models LLM Inference Engine Algorithm 115

Marktechpost

OCTOBER 24, 2024

In PROVE, researchers use a high-fidelity scene graph representation constructed from hyper-detailed image captions and employ a large language model (LLM) to generate diverse question-answer (QA) pairs along with executable programs to verify each QA pair. This approach allows the creation of a benchmark dataset of 10.5k

AI Research 121

AI Research AI Researcher Inference Engine Large Language Models 121

Marktechpost

OCTOBER 19, 2024

Large language models (LLMs) like GPT-4, Gemini, and Llama 3 have revolutionized natural language processing through extensive pre-training and supervised fine-tuning (SFT). However, these models come with high computational costs for training and inference. Check out the Paper. If you like our work, you will love our newsletter.

Large Language Models 115

Large Language Models Inference Engine Natural Language Processing LLM 115

Marktechpost

OCTOBER 25, 2024

In light of these drawbacks, a trustworthy technique for determining when and how an LLM may be unsure about its capacity to follow directions is necessary to reduce the dangers involved with using these models. Also, don’t forget to follow us on Twitter and join our Telegram Channel and LinkedIn Gr oup.

LLM 103

LLM Inference Engine Large Language Models ML 103

Marktechpost

OCTOBER 21, 2024

By combining layer dropout, early exit loss, and self-speculative decoding, the researchers have proposed a novel approach that not only speeds up inference but also reduces memory requirements, making it feasible for large models to be deployed on commodity hardware. Check out the Paper , Model Series on Hugging Face , and GitHub.

Large Language Models 116

Large Language Models Inference Engine AI AI 116

Marktechpost

OCTOBER 28, 2024

In current practice, traditional methods of KG construction rely heavily on LLM prompting to derive knowledge triplets. A distilled model, Distill-SynthKG , was further developed by fine-tuning a smaller LLM using KGs generated from SynthKG. This efficiency is evident in the Graph+LLM retriever, where the KG model demonstrated a 15.2%

LLM 109

LLM Inference Engine Large Language Models Artificial Intelligence 109

Marktechpost

OCTOBER 17, 2024

Task superposition means that when an LLM is provided relevant examples for each task within the same input prompt, it can process and produce responses for several tasks at once. The team has shared their primary contributions as follows. Llama-3, and Qwen. If you like our work, you will love our newsletter.

Large Language Models 111

Large Language Models Inference Engine LLM ML 111

Marktechpost

OCTOBER 19, 2024

The study also employed regularization schemes like Negative Log-Likelihood (NLL) to mitigate over-optimization and evaluated generalization performance using LLM-as-a-Judge, a framework for comparing model outputs with those from other leading models. If you like our work, you will love our newsletter.

Inference Engine 111

Inference Engine Algorithm LLM ML 111

Marktechpost

OCTOBER 16, 2024

The Attack Generation and Exploration Module uses an attacker LLM to generate jailbreak prompts based on strategies from the Retrieval Module. These prompts target a victim LLM, with responses evaluated by a scorer LLM. This process generates attack logs for the Strategy Library Construction Module.

Large Language Models 116

Large Language Models Inference Engine LLM Algorithm 116

Marktechpost

OCTOBER 22, 2024

A team of researchers from Carnegie Mellon University introduced PANGEA, a multilingual multimodal LLM designed to bridge linguistic and cultural gaps in visual understanding tasks. PANGEA is trained on a newly curated dataset, PANGEAINS, which contains 6 million instruction samples across 39 languages.

Large Language Models 110

Large Language Models Data Scarcity Inference Engine LLM 110

Marktechpost

OCTOBER 18, 2024

Current evaluation frameworks, such as LLM-as-a-Judge, which uses large language models to judge outputs from other AI systems, must account for the entire task-solving process. The results of the Agent-as-a-Judge framework achieved a 90% alignment with human evaluators, compared to LLM-as-a-Judge’s 70% alignment.

Large Language Models 111

Large Language Models LLM AI Developer AI Development 111

Marktechpost

OCTOBER 18, 2024

One of the critical problems faced by AI researchers is that many current methods for enhancing LLM reasoning capabilities rely heavily on human intervention. Finally, the LLM uses these reasoning structures to create detailed reasoning paths. If you like our work, you will love our newsletter.

Large Language Models 115

Large Language Models Inference Engine AI AI 115

Marktechpost

OCTOBER 22, 2024

GenRM leverages a large pre-trained LLM to generate reasoning chains that help decision-making. The model also outperformed LLM-based judges, which rely solely on AI feedback, showcasing a more balanced approach to feedback optimization. Also, don’t forget to follow us on Twitter and join our Telegram Channel and LinkedIn Gr oup.

Inference Engine 119

Inference Engine Large Language Models LLM AI 119

Marktechpost

OCTOBER 18, 2024

Traditionally, large language models (LLMs) used for building TTS pipelines convert speech to text using automatic speech recognition (ASR), process it using an LLM, and then convert the output back to speech via TTS. Also, don’t forget to follow us on Twitter and join our Telegram Channel and LinkedIn Gr oup.

Inference Engine 122

Inference Engine Large Language Models AI AI 122

Marktechpost

OCTOBER 20, 2024

This is indeed a very serious challenge for the larger and more effective scaling of LLM modalities applied to real-world applications. Current solutions to alignment involve methods such as RLHF and direct preference optimization (DPO). Also, don’t forget to follow us on Twitter and join our Telegram Channel and LinkedIn Gr oup.

Inference Engine 110

Inference Engine LLM Large Language Models ML 110

Marktechpost

OCTOBER 18, 2024

Researchers from Westlake University and Zhejiang University introduced an omni-modal LLM Baichuan-Omni alongside a multimodal training scheme designed to facilitate advanced multimodal processing and better user interactions. It also provides multilingual support for languages such as English and Chinese.

Large Language Models 114

Large Language Models Inference Engine Natural Language Processing LLM 114

Marktechpost

OCTOBER 27, 2024

The disconnect between laboratory performance and practical applications raises concerns about the true effectiveness of LLM-based provers. Current methodologies often fail to capture the intricate nature of mathematical reasoning required in authentic theorem-proving scenarios, limiting their practical utility.

Large Language Models 102

Large Language Models Metadata Inference Engine Automation 102

Marktechpost

OCTOBER 21, 2024

While alternative methods like large language model (LLM)-based encoders can handle longer sequences, they fail to provide the same level of alignment as contrastive pre-training encoders do. The growing popularity of diffusion models has been driven by advancements in fast sampling techniques and text-conditioned generation.

Inference Engine 115

Inference Engine Large Language Models LLM ML 115

Towards AI

JULY 1, 2024

Last Updated on July 3, 2024 by Editorial Team Author(s): Suhaib Arshad Originally published on Towards AI. The field of generative AI has been seeing exponential development in recent years, from LLMs to text-to-image models and upcoming text-to-video models. Now that we have the API key, let’s get started.

Generative AI 98

Generative AI Inference Engine Large Language Models OpenAI 98

Marktechpost

OCTOBER 26, 2024

Methods for testing reasoning capabilities include datasets like GSM8k, which contains arithmetic word problems that test LLMs on basic to intermediate logic tasks. However, these benchmarks must be revised to push the limits of LLM reasoning, as they often contain repetitive patterns and need more variety in problem structures.

Inference Engine 104

Inference Engine LLM Large Language Models Machine Learning 104

Marktechpost

OCTOBER 21, 2024

The technology behind MIND works by prompting an LLM with a raw text from OpenWebMath and instructing it to break down the problem into a series of conversational turns. Each conversation style contributes to decomposing a mathematical problem into its core components, allowing the model to focus on each part in a detailed and logical manner.

Large Language Models 115

Large Language Models Inference Engine AI AI 115

Marktechpost

OCTOBER 19, 2024

These methods rely on predefined rules or LLM (Large Language Model) judgments to identify potential vulnerabilities in code. The second stage uses LLM-based mutators to generate large-scale data from these seed samples, preserving the original security context. These samples contain insecure and patched code and associated test cases.

Inference Engine 105

Inference Engine Large Language Models LLM AI Modeling 105

Marktechpost

OCTOBER 21, 2024

A team of researchers from Microsoft Responsible AI Research and Johns Hopkins University proposed Controllable Safety Alignment (CoSA) , a framework for efficient inference-time adaptation to diverse safety requirements. The adapted strategy first produces an LLM that is easily controllable for safety.

Large Language Models 105

Large Language Models Inference Engine LLM AI 105

Marktechpost

OCTOBER 27, 2024

This adaptation is essential, given the global user base that increasingly relies on LLMs across diverse languages for various tasks, including everyday information, safety guidelines, and nuanced conversations. A core issue in LLM development lies in adapting RMs to perform consistently across different languages.

Inference Engine 106

Inference Engine Large Language Models LLM ML 106

Marktechpost

OCTOBER 15, 2024

These problems are particularly noticeable when deploying LLMs on NVIDIA Hopper GPUs, as balancing memory usage and computational speed becomes more challenging. Neural Magic introduces Machete: a new mixed-input GEMM kernel for NVIDIA Hopper GPUs, representing a major advancement in high-performance LLM inference.

LLM 69

LLM Inference Engine Large Language Models ML 69

Marktechpost

OCTOBER 17, 2024

This research offers a valuable tool for improving the quality and reliability of LLM-generated code and streamlining software development workflows. This approach is quite comprehensive but provides a setback due to its dependence on predefined tests that limit the adaptability in unconventional coding styles. Check out the Paper.

Machine Learning 69

Machine Learning Software Development Inference Engine Large Language Models 69

Marktechpost

OCTOBER 26, 2024

In RAG systems, an LLM creates a response based on the recovered content after a retrieval step in which pertinent information or passages are gathered. The second kind, known as arena-based benchmarks, uses a high-performance LLM as a teacher to evaluate model outputs through direct model comparisons in a setting akin to a competition.

LLM 64

LLM Inference Engine Large Language Models Machine Learning 64

Marktechpost

OCTOBER 22, 2024

SynPO is a self-boosting method that enhances LLM alignment without heavily depending on human annotations by creating synthetic data. Instead of relying on complicated datasets or outside human inputs, it makes use of the LLM itself to provide a range of cues that elicit various scenarios and replies. and ArenaHard.

LLM 59

LLM Inference Engine Large Language Models ML 59

Marktechpost

OCTOBER 17, 2024

Large Language Model (LLM)–based online agents have significantly advanced in recent times, resulting in unique designs and new benchmarks that show notable improvements in autonomous web navigation and interaction. Also, don’t forget to follow us on Twitter and join our Telegram Channel and LinkedIn Gr oup.

Inference Engine 64

Inference Engine Large Language Models LLM AI 64

Marktechpost

OCTOBER 20, 2024

None of these traditional approaches capture key metrics, such as how much time programmers spend coding, how frequently programmers accept LLM suggestions or the degree to which LLMs actually help solve complex problems. Also, don’t forget to follow us on Twitter and join our Telegram Channel and LinkedIn Gr oup.

LLM 64

LLM Inference Engine Large Language Models ML 64