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Diving back into the classic "Language Models are Few-Shot Learners" paper (the GPT-3 paper) and it's still a goldmine for anyone in NLP. It really set the stage for so much of what we're seeing today. Here’s a thread on why it’s still a must-read. 🧵 #NLProc #AI
arxivlens.com/PaperView/De...
Language Models are Few-Shot Learners - AI Research Paper Analysis | ArxivLens
AI-powered analysis of 'Language Models are Few-Shot Learners'. Recent work has demonstrated substantial gains on many NLP tasks and benchmarks by pre-training on a large corpus of text followed by ...
arxivlens.com
The original GAN paper was rejected from a major conference. Reviewers didn't get it. One year later, GANs were everywhere. Ian Goodfellow's "two networks fighting each other" idea went from "too weird" to "revolutionizing generative AI." Never let rejection stop you.
November 11, 2025 at 2:02 PM
EfficientNet (2019) asked a simple question: how do you scale neural networks optimally? Width? Depth? Resolution? Answer: all three, carefully balanced. Result? Better accuracy with 10x fewer parameters. Compound scaling became the blueprint for efficient model design.
November 10, 2025 at 2:01 PM
"Deep Learning" (Hinton, LeCun, Bengio, Nature 2015) wasn't just a paper—it was a declaration of victory. The three godfathers of AI explained how deep learning conquered speech, vision, and language. Published in Nature, legitimizing AI in the eyes of mainstream science. The paper that said "we tol
November 9, 2025 at 2:01 PM
MobileNet (2017) proved bigger isn't always better. Google's depthwise separable convolutions slashed model size by 75% with minimal accuracy loss. Now your phone can run image recognition locally. The paper that put AI in your pocket instead of the cloud.
November 8, 2025 at 2:00 PM
Inverse-Designed Grating Couplers with Tunable Wavelength via Scaling
and Biasing
Fabian Becker, Kai Müller et al.
Paper
Details
#InverseDesignGratingCouplers #TunableWavelengthOptics #ScalingAndBiasingInPhotonics
November 7, 2025 at 5:01 PM
X-ray and UV Observations of the Young Sun HIP~67522: Evidence of
Lyman-alpha Absorption Within the Planetary System
Alexander Brown, Allison Youngblood et al.
Paper
Details
#YoungSunHIP67522 #LymanAlphaAbsorption #PlanetarySystemXrayUV
November 7, 2025 at 5:01 PM
A Next-Generation Exoplanet Atmospheric Retrieval Framework NEXOTRANS
for Emission Spectroscopy: New Constraints and Atmospheric Characterization
of WASP-69b Using JWST NIRCam and MIRI Observations
Debayan Das, Liton Majumdar et al.
Paper
Details
November 7, 2025 at 5:01 PM
Ionospheric responses over the Antarctic region to Intense Space Weather
events: Plasma Convection vs. Auroral Precipitation
Gopi K. Seemala, Sumanjit Chakraborty
Paper
Details
#IonosphericResponses #SpaceWeatherAntarctic #PlasmaConvectionAurora
November 7, 2025 at 5:01 PM
Assessing the metal and rare earth element mining potential of
undifferentiated asteroids through the study of carbonaceous chondrites
Jacinto Alonso-Azcárate, Jordi Ibáñez-Insa et al.
Paper
Details
#AsteroidMining #RareEarthElements #CarbonaceousChondrites
November 7, 2025 at 5:01 PM
Stacking transmission spectra of different exoplanets
James E. Owen, James Kirk
Paper
Details
#ExoplanetSpectra #TransmissionSpectroscopy #AstroResearch
November 7, 2025 at 5:01 PM
A Decade of Solar High-Fidelity Spectroscopy and Precise Radial
Velocities from HARPS-N
A. Anna John, A. Collier Cameron et al.
Paper
Details
#HARPSN #SolarSpectroscopy #ExoplanetResearch
November 7, 2025 at 5:00 PM
Diurnal Variations of Lee Wave Clouds on Mars using Emirates eXploration
Imager (EXI)
Mariam R. Alshamsi, Mashhoor A. Al-Wardat
Paper
Details
#MarsLeeWaveClouds #EXIImager #MarsExplorationResearch
November 7, 2025 at 5:00 PM
The Perceptron (1958) was AI's first hype cycle. Rosenblatt's algorithm could learn to classify! The Navy funded it! Then Minsky proved it couldn't solve XOR and triggered the first AI winter. Took 30 years for neural networks to recover. The OG boom-and-bust story.
November 7, 2025 at 2:01 PM
Simplex-to-Euclidean Bijections for Categorical Flow Matching
Arto Klami, Bernardo Williams et al.
Paper
Details
#SimplexToEuclideanBijections #CategoricalFlowMatching #GeometricDataAnalysis
November 6, 2025 at 5:02 PM
Active transfer learning for structural health monitoring
A. J. Hughes, J. Poole et al.
Paper
Details
#StructuralHealthMonitoring #TransferLearning #SmartInfrastructure
November 6, 2025 at 5:02 PM
AstuteRAG-FQA: Task-Aware Retrieval-Augmented Generation Framework for
Proprietary Data Challenges in Financial Question Answering
Khandoker Ashik Uz Zaman, Mahdi H. Miraz et al.
Paper
Details
#FinancialQA #RAGFramework #TaskAwareRetrieval
November 6, 2025 at 5:02 PM
ORGEval: Graph-Theoretic Evaluation of LLMs in Optimization Modeling
Angyang Gu, Congliang Chen et al.
Paper
Details
#ORGEval #GraphTheory #LargeLanguageModels
November 6, 2025 at 5:01 PM
Sybil-Resistant Service Discovery for Agent Economies
David Shi, Kevin Joo
Paper
Details
#SybilResistantDiscovery #AgentEconomies #DecentralizedSystems
November 6, 2025 at 5:01 PM
Community Detection on Model Explanation Graphs for Explainable AI
Ehsan Moradi
Paper
Details
#ExplainableAI #ModelExplanationGraphs #CommunityDetection
November 6, 2025 at 5:01 PM
Nonisospectral deformations of noncommutative Laurent biorthogonal
polynomials and matrix discrete Painlevé-type equations
Dan Dai, Xiaolu Yue
Paper
Details
#NoncommutativeMath #DiscretePainleveEquations #LaurentPolynomials
November 6, 2025 at 5:01 PM
Lieb-Robinson bounds in classical oscillating lattice systems
C. J. F. van de Ven, Ian Koot
Paper
Details
#LiebRobinsonBounds #ClassicalOscillatingLatticeSystems #QuantumClassicalCorrespondence
November 6, 2025 at 5:01 PM
Quantum waste management: Utilizing residual states in quantum
information processing
Chirag Srivastava, Karol Horodecki et al.
Paper
Details
#QuantumWasteManagement #QuantumInformationProcessing #ResidualStatesResearch
November 6, 2025 at 5:01 PM
Brightness variability in polar circumbinary disks
Giuseppe Lodato, Ian Rabago et al.
Paper
Details
#PolarCircumbinaryDisks #BrightnessVariability #AstrophysicsResearch
November 6, 2025 at 5:01 PM
Batch Normalization (2015) is the "turn it off and on again" of deep learning. By normalizing layer inputs during training, it made networks train 10x faster and way more stable. One technique, thousands of hours saved. Sometimes the best innovations are embarrassingly simple.
November 6, 2025 at 2:01 PM
Generating Accurate and Detailed Captions for High-Resolution Images
Dogun Kim, Gawon Seo et al.
Paper
Details
#ImageCaptioning #HighResolutionImaging #AIResearch
November 5, 2025 at 5:02 PM