A Survey on Deep Learning for Theorem Proving Zhaoyu Li, Jialiang Sun, Logan Murphy, Qidong Su, Zenan Li, Xian Zhang, Kaiyu Yang, Xujie Si CONFERENCE ON LANGUAGE MODELING|October 2024 Theorem proving is a fundamental aspect of mathematics, spanning from informal reasoning in natural lan...
A Deep Reinforcement Learning Approach to First-Order Logic Theorem Proving.Maxwell CrouseIbrahim AbdelazizBassem MakniSpencer WhiteheadCristina CornelioPavan KapanipathiKavitha SrinivasVeronika ThostMichael WitbrockAchille FokoueNational Conference on Artificial Intelligence...
In [40], three methods for DDoS attack detection in the IoT based on specific network behavior (feature extraction), SDN-based network architecture [41, 42], and a third approach from Apache Spark, which is a platform for DDoS attack detection in the IoT through machine learning were present...
the supreme academic the supreme court of the surgeon muttered the survey showed the svn the sweetest one the sweetest romance the sweetheart season the swimmers the swiss music fair the switch name the swod of dakness the syllables get pum the synthesis and stu the synthesizing the system adm...
Modulus Labs: bringing powerful ML models on-chain and their blogs ZKML: Bridging AI/ML and Web3 with Zero-Knowledge Proofs zkonduit: inference for deep learning models and other computational graphs in a zk-snark ZK Machine Learning: truly private machine learning, with zk-SNARKs and blockch...
The paper provides an introductory survey of Explanation-Based Learning (EBL). It attempts to define EBL's position in AI by exploring its relationship to other AI techniques, including other sub-fields of machine learning. Further issues discussed include the form of learning exhibited by EBL and...
4) Mathematical LLMs - a survey on the progress of LLMs on mathematical tasks; covers papers and resources on LLM research around prompting techniques and tasks such as math word problem-solving and theorem proving. Paper, Tweet 5) Towards Fully Transparent Open-Source LLMs - proposes LLM360...
Research Safety for Intelligent and Connected Vehicles—ReviewA Survey on an Emerging Safety Challenge for Autonomous Vehicles: Safety of the Intended Functionality Author links open overlay panelHong Wang a, Wenbo Shao a, Chen Sun b, Kai Yang c, Dongpu Cao b, Jun Li aShow more Add to ...
We observe an intriguing phenomenon which we call cliff-learning. Cliff-learning refers to regions of data-scaling laws where performance improves at a faster than power law rate (i.e. regions of concavity on a log-log scaling plot). Empirical Study: 2022 ModelDiff: A Framework for ...
Collecting awesome papers of RAG for AIGC. We propose a taxonomy of RAG foundations, enhancements, and applications in paper "Retrieval-Augmented Generation for AI-Generated Content: A Survey". - hymie122/RAG-Survey