Copertina

That Chip Has Sailed: A Critique of Unfounded Skepticism Around AI for Chip Design

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Goldie, Anna, Mirhoseini, Azalia, Dean, Jeff
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Artificial Intelligence Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Synthetic Data Generation & Multi-Step RL for Reasoning & Tool Use
di: Goldie, Anna, et al.
Pubblicazione: (2025)

ForTIFAI: Fending Off Recursive Training Induced Failure for AI Model Collapse
di: Shabgahi, Soheil Zibakhsh, et al.
Pubblicazione: (2025)

On the Role of Temperature Sampling in Test-Time Scaling
di: Wu, Yuheng, et al.
Pubblicazione: (2025)

Agent JIT Compilation for Latency-Optimizing Web Agent Planning and Scheduling
di: Winston, Caleb, et al.
Pubblicazione: (2026)

Think, Prune, Train, Improve: Scaling Reasoning without Scaling Models
di: Costello, Caia, et al.
Pubblicazione: (2025)

SPRINT: Enabling Interleaved Planning and Parallelized Execution in Reasoning Models
di: Biju, Emil, et al.
Pubblicazione: (2025)

CHESS: Contextual Harnessing for Efficient SQL Synthesis
di: Talaei, Shayan, et al.
Pubblicazione: (2024)

Large Language Monkeys: Scaling Inference Compute with Repeated Sampling
di: Brown, Bradley, et al.
Pubblicazione: (2024)

Multimodal Chip Physical Design Engineer Assistant
di: Tsai, Yun-Da, et al.
Pubblicazione: (2025)

Artificial Intelligence-Driven Network-on-Chip Design Space Exploration: Neural Network Architectures for Design
di: N, Amogh Anshu, et al.
Pubblicazione: (2025)

Chip Placement with Diffusion Models
di: Lee, Vint, et al.
Pubblicazione: (2024)

Exploring Diffusion Transformer Designs via Grafting
di: Chandrasegaran, Keshigeyan, et al.
Pubblicazione: (2025)

How Do Large Language Monkeys Get Their Power (Laws)?
di: Schaeffer, Rylan, et al.
Pubblicazione: (2025)

KernelBench: Can LLMs Write Efficient GPU Kernels?
di: Ouyang, Anne, et al.
Pubblicazione: (2025)

MATADOR: Automated System-on-Chip Tsetlin Machine Design Generation for Edge Applications
di: Rahman, Tousif, et al.
Pubblicazione: (2024)

ChipExpert: The Open-Source Integrated-Circuit-Design-Specific Large Language Model
di: Xu, Ning, et al.
Pubblicazione: (2024)

HiVeGen -- Hierarchical LLM-based Verilog Generation for Scalable Chip Design
di: Tang, Jinwei, et al.
Pubblicazione: (2024)

FlowPlace: Flow Matching for Chip Placement
di: Xie, Peng, et al.
Pubblicazione: (2026)

Reasoning-SQL: Reinforcement Learning with SQL Tailored Partial Rewards for Reasoning-Enhanced Text-to-SQL
di: Pourreza, Mohammadreza, et al.
Pubblicazione: (2025)

OpenJarvis: Personal AI, On Personal Devices
di: Saad-Falcon, Jon, et al.
Pubblicazione: (2026)

On-Chip Hardware-Aware Quantization for Mixed Precision Neural Networks
di: Huang, Wei, et al.
Pubblicazione: (2023)

Cartridges: Lightweight and general-purpose long context representations via self-study
di: Eyuboglu, Sabri, et al.
Pubblicazione: (2025)

Deep Reinforcement Learning for System-on-Chip: Myths and Realities
di: Sung, Tegg Taekyong, et al.
Pubblicazione: (2022)

Astra: A Multi-Agent System for GPU Kernel Performance Optimization
di: Wei, Anjiang, et al.
Pubblicazione: (2025)

M2RU: Memristive Minion Recurrent Unit for On-Chip Continual Learning at the Edge
di: Zyarah, Abdullah M., et al.
Pubblicazione: (2025)

Archon: An Architecture Search Framework for Inference-Time Techniques
di: Saad-Falcon, Jon, et al.
Pubblicazione: (2024)

DOCTOR: Dynamic On-Chip Temporal Variation Remediation Toward Self-Corrected Photonic Tensor Accelerators
di: Lu, Haotian, et al.
Pubblicazione: (2024)

Large Language Models are Skeptics: False Negative Problem of Input-conflicting Hallucination
di: Song, Jongyoon, et al.
Pubblicazione: (2024)

Scalable Oversight for Superhuman AI via Recursive Self-Critiquing
di: Wen, Xueru, et al.
Pubblicazione: (2025)

Sailor2: Sailing in South-East Asia with Inclusive Multilingual LLMs
di: Dou, Longxu, et al.
Pubblicazione: (2025)

The False Dawn: Reevaluating Google's Reinforcement Learning for Chip Macro Placement
di: Markov, Igor L.
Pubblicazione: (2023)

Matryoshka Quantization
di: Nair, Pranav, et al.
Pubblicazione: (2025)

BBOPlace-Bench: Benchmarking Black-Box Optimization for Chip Placement
di: Xue, Ke, et al.
Pubblicazione: (2025)

Hidden-State Privacy Has an Empty Middle
di: Bell, Alexander Okezue
Pubblicazione: (2026)

TRACE: Capability-Targeted Agentic Training
di: Kang, Hangoo, et al.
Pubblicazione: (2026)

Enabling Efficient Processing of Spiking Neural Networks with On-Chip Learning on Commodity Neuromorphic Processors for Edge AI Systems
di: Putra, Rachmad Vidya Wicaksana, et al.
Pubblicazione: (2025)

Self-Supervised Learning for Time Series: A Review & Critique of FITS
di: Eefsen, Andreas Løvendahl, et al.
Pubblicazione: (2024)

Agentic AI for Commercial Insurance Underwriting with Adversarial Self-Critique
di: Roy, Joyjit, et al.
Pubblicazione: (2026)

Abstraction for Offline Goal-Conditioned Reinforcement Learning
di: Wibault, Clarisse, et al.
Pubblicazione: (2026)

Interactive Critique-Revision Training for Reliable Structured LLM Generation
di: Yu, Fei Xu, et al.
Pubblicazione: (2026)