HN signa11 3/16/2026

Before AI's Kepler Moment – Are LLMs the Epicycles of Intelligence?

Critical analysis comparing LLMs to epicycles in astronomy, questioning whether intelligence is the appropriate metric for evaluating current language models.

HN gordonmattey 3/16/2026

Show HN: Port42 – AI companions that build and act on your Mac (v0.5.0)

Port42: SwiftUI app enabling AI companions to build interactive UIs and act on macOS. Open source developer tool with live code demo.

HN vismit2000 3/16/2026

What Is an Agent Harness?

Agent harness concept: software infrastructure wrapping LLMs/agents for orchestrating tools, memory, workflows. Technical introduction with architectural focus.

HN teleforce 3/16/2026

Agentic Trust Framework (ATF)

Agentic Trust Framework: open security specification for Zero Trust governance of autonomous AI agents. Standards and governance for agent deployment.

HN veeceey 3/16/2026

BotStadium – AI agents compete on live sports predictions in real-time

BotStadium: research platform simulating AI agent behavior through competitive sports predictions. Agent behavior analysis and testing platform.

LB sebastianraschka.com via refi64 3/16/2026

LLM Architecture Gallery

LLM Architecture Gallery: curated collection of architecture diagrams and specifications for major LLMs. Technical reference resource.

Ax Selim Furkan Tekin, Yichang Xu, Gaowen Liu, Ramana Rao Kompella, Margaret L. Loper, Ling Liu 3/16/2026

Vision Verification Enhanced Fusion of VLMs for Efficient Visual Reasoning

Multi-VLM ensemble method using vision and language modalities to select complementary models for efficient visual reasoning.

Ax Sihao Ding 3/16/2026

Colluding LoRA: A Composite Attack on LLM Safety Alignment

Composite attack on LLM safety alignment where multiple LoRA adapters appear benign individually but suppress safety when composed.

Ax Nandish Chattopadhyay, Anadi Goyal, Chandan Karfa, Anupam Chattopadhyay 3/16/2026

STRAP-ViT: Segregated Tokens with Randomized -- Transformations for Defense against Adversarial Patches in ViTs

Defense mechanism against adversarial patches in Vision Transformers using token segregation and randomized transformations.

Ax Chaojie Sun, Bin Cao, Tiantian Li, Chenyu Hou, Ruizhe Li, Qing Fan 3/16/2026

FGTR: Fine-Grained Multi-Table Retrieval via Hierarchical LLM Reasoning

Hierarchical LLM-based approach for fine-grained multi-table retrieval using compositional reasoning instead of coarse-grained similarity matching.

Ax Yali Du, San-Zhuo Xi, Hui Sun, Ming Li 3/16/2026

Design-Specification Tiling for ICL-based CAD Code Generation

In-context learning strategy for CAD code generation using design-specification tiling to improve LLM performance on domain-specific tasks.

Ax Jillur Rahman Saurav, Thuong Le Hoai Pham, Pritam Mukherjee, Paul Yi, Brent A. Orr, Jacob M. Luber 3/16/2026

UNIStainNet: Foundation-Model-Guided Virtual Staining of H&E to IHC

Foundation model-guided approach for virtual immunohistochemistry staining from H&E images to accelerate pathology diagnostics.

Ax Yonghun Jeong, David Yoon Suk Kang, Yeon-Chang Lee 3/16/2026

Anchored Alignment: Preventing Positional Collapse in Multimodal Recommender Systems

Multimodal recommendation framework using anchor-based alignment in projection space to prevent modality collapse and ID dominance.

Ax Yuchen Hua, Xingang Peng, Jianzhu Ma, Muhan Zhang 3/16/2026

VecMol: Vector-Field Representations for 3D Molecule Generation

Novel 3D molecule generation framework using vector-field representations to address modality entanglement and geometry-chemistry constraints.

Ax James Akl, Jose Nicolas Avendano Arbelaez, James Barabas, Jennifer L. Barry, Kalie Ching, Noam Eshed, Jiahui Fu, Michel Hidalgo, Andrew Hoelscher, Tushar Kusnur, Andrew Messing, Zachary Nagler, Brian Okorn, Mauro Passerino, Tim J. Perkins, Eric Rosen, Ankit Shah, Tanmay Shankar, Scott Shaw 3/16/2026

Show, Don't Tell: Detecting Novel Objects by Watching Human Videos

Self-supervised system for robots to detect and recognize novel objects from human video demonstrations without prompt engineering.

Ax Jiaming Zhang, Yuyuan Li, Xiaohua Feng, Li Zhang, Longfei Li, Jun Zhou, Chaochao Chen 3/16/2026

Taming the Long Tail: Efficient Item-wise Sharpness-Aware Minimization for LLM-based Recommender Systems

Efficient optimization technique addressing long-tail distribution problem in LLM-based sequential recommender systems.

Ax Nazar Puriy, Johannes Jakubik, Benedikt Blumenstiel, Konrad Schindler 3/16/2026

TerraFlow: Multimodal, Multitemporal Representation Learning for Earth Observation

Multimodal foundation model for Earth observation using temporal training objectives robust to variable-length satellite and sensor data.

Ax Zezhou Zhang, Songxin Zhang, Xiao Xiong, Junjie Zhang, Zejian Xie, Jingyi Xi, Zunyao Mao, Zan Mao, Zhixin Mai, Zhuoyang Song, Jiaxing Zhang 3/16/2026

PVI: Plug-in Visual Injection for Vision-Language-Action Models

Method for injecting auxiliary visual features into vision-language-action models to improve geometric understanding and temporal reasoning for robotic manipulation.

Ax Zhuchenyang Liu, Yao Zhang, Yu Xiao 3/16/2026

NanoVDR: Distilling a 2B Vision-Language Retriever into a 70M Text-Only Encoder for Visual Document Retrieval

Model distillation approach compressing 2B vision-language retriever into 70M text-only encoder for efficient document retrieval.

Ax You Wu, Zhenguo Wang, Naiyu Wang 3/16/2026

From AI Weather Prediction to Infrastructure Resilience: A Correction-Downscaling Framework for Tropical Cyclone Impacts

AI-based framework transforming global weather forecasts into fine-grained wind field predictions and infrastructure failure probabilities for tropical cyclones.

Ax Shaofeng Guo, Jiequan Cui, Richang Hong 3/16/2026

Rethinking VLMs for Image Forgery Detection and Localization

Research on using vision-language models for detecting and localizing forged images, studying how VLM priors affect forgery detection performance.

Ax Yamin Arefeen, Sidharth Kumar, Steven Warach, Hamidreza Saber, Jonathan Tamir 3/16/2026

Accelerating Stroke MRI with Diffusion Probabilistic Models through Large-Scale Pre-training and Target-Specific Fine-Tuning

Data-efficient MRI reconstruction strategy using diffusion probabilistic models with pre-training and fine-tuning.

Ax Matthew Butler, Yi Fan, Christos Faloutsos 3/16/2026

FraudFox: Adaptable Fraud Detection in the Real World

Adaptable fraud detection system handling adversarial attacks in resource-constrained environments with multiple risk modules.

Ax Bangjun Xiao, Yihao Zhao, Xiangwei Deng, Shihua Yu, Yuxing Xiang, Huaqiu Liu, Qiying Wang, Liang Zhao, Hailin Zhang, Xuanzhe Liu, Xin Jin, Fuli Luo 3/16/2026

ARL-Tangram: Unleash the Resource Efficiency in Agentic Reinforcement Learning

Framework (ARL-Tangram) optimizing resource efficiency in agentic RL by dynamically allocating external compute resources.

Ax Sampath Rapuri, Lalithkumar Seenivasan, Dominik Schneider, Roger Soberanis-Mukul, Yufan He, Hao Ding, Jiru Xu, Chenhao Yu, Chenyan Jing, Pengfei Guo, Daguang Xu, Mathias Unberath 3/16/2026

SAW: Toward a Surgical Action World Model via Controllable and Scalable Video Generation

Surgical world model using controllable video generation for simulating surgical actions with precise tool-tissue control.

Ax Tianhao Fu, Bingxuan Yang, Juncheng Guo, Shrena Sribalan, Yucheng Chen 3/16/2026

SortScrews: A Dataset and Baseline for Real-time Screw Classification

Dataset and baseline for real-time screw classification in industrial automation and robotic systems.

Ax Yanpeng Zhao, Wentao Ding, Hongtao Li, Baoxiong Jia, Zilong Zheng 3/16/2026

ESPIRE: A Diagnostic Benchmark for Embodied Spatial Reasoning of Vision-Language Models

Diagnostic benchmark (ESPIRE) for evaluating vision-language models on embodied spatial reasoning tasks.

Ax Mingyu Deng, Shengqian Han 3/16/2026

Association-Aware GNN for Precoder Learning in Cell-Free Systems

GNN approach for precoder learning in cell-free wireless systems accounting for dynamic user-access point associations.

Ax Steven Motta, Gioele Nanni 3/16/2026

Federated Few-Shot Learning on Neuromorphic Hardware: An Empirical Study Across Physical Edge Nodes

Empirical study of federated few-shot learning on neuromorphic hardware using spike-timing-dependent plasticity.

Ax Noel Smith, Andrzej Ruszczynski 3/16/2026

Convergence Rate of a Functional Learning Method for Contextual Stochastic Optimization

Convergence analysis of functional learning methods for contextual stochastic optimization problems.

Ax Pierre Moreau, Emeline Pineau Ferrand, Yann Choho, Benjamin Wong, Annabelle Blangero, Milan Bhan 3/16/2026

Towards Faithful Multimodal Concept Bottleneck Models

Research on interpretable multimodal concept bottleneck models ensuring faithful explanations through proper concept detection.

Ax Xiangyu Liu, Kaiqing Zhang 3/16/2026

Partially Observable Multi-Agent Reinforcement Learning with Information Sharing

Provable multi-agent reinforcement learning in partially observable stochastic games leveraging information sharing among agents.

Ax Wasu Top Piriyakulkij, Yingheng Wang, Volodymyr Kuleshov 3/16/2026

Denoising Diffusion Variational Inference: Diffusion Models as Expressive Variational Posteriors

Introduces diffusion models as expressive variational posteriors for black-box inference in latent variable models.

Ax Alejandro Parada-Mayorga, Alejandro Ribeiro 3/16/2026

Sampling and Uniqueness Sets in Graphon Signal Processing

Graph signal processing research extending sampling theory to graphon signals using limits of large graphs.

Ax Jeonghye Kim, Suyoung Lee, Woojun Kim, Youngchul Sung 3/16/2026

Adaptive $Q$-Aid for Conditional Supervised Learning in Offline Reinforcement Learning

Research on offline reinforcement learning combining return-conditioned supervised learning with Q-functions to improve stitching capability and stability.

Ax Yinan Huang, Haoyu Wang, Pan Li 3/16/2026

What Are Good Positional Encodings for Directed Graphs?

Introduces Walk Profile method and explores positional encodings for directed graphs in graph neural networks and graph transformers.

Ax Hemanth Saratchandran, Jianqiao Zheng, Yiping Ji, Wenbo Zhang, Simon Lucey 3/16/2026

Rethinking Attention: Polynomial Alternatives to Softmax in Transformers

Explores polynomial attention alternatives to softmax in transformers, arguing regularization rather than probability distribution drives performance.

Ax Antoine Moulin, Gergely Neu, Luca Viano 3/16/2026

Optimistically Optimistic Exploration for Provably Efficient Infinite-Horizon Reinforcement and Imitation Learning

Proposes first computationally efficient algorithm with optimal regret for infinite-horizon discounted reinforcement and imitation learning.

Ax Ruta Binkyte, Ivaxi Sheth, Zhijing Jin, Mohammad Havaei, Bernhard Sch\"olkopf, Mario Fritz 3/16/2026

Causality Is Key to Understand and Balance Multiple Goals in Trustworthy ML and Foundation Models

Advocates integrating causal methods into ML to balance trustworthiness objectives like fairness, privacy, robustness, and explainability.

Ax Heng-Sheng Chang, Prashant G. Mehta 3/16/2026

Dual Filter: A Transformer-like Inference Architecture for Hidden Markov Models

Proposes Dual Filter framework connecting Hidden Markov Models to transformer decoder architecture for causal nonlinear prediction.

Ax Yueheng Li, Guangming Xie, Zongqing Lu 3/16/2026

Guided Policy Optimization under Partial Observability

Introduces Guided Policy Optimization framework for RL in partially observable environments using privileged information from simulators.

Ax Nicolas Keriven 3/16/2026

Backward Oversmoothing: why is it hard to train deep Graph Neural Networks?

Analyzes oversmoothing problem in deep Graph Neural Networks and explores why networks fail to learn non-oversmoothed representations.

Ax Lakshita Dodeja, Karl Schmeckpeper, Shivam Vats, Thomas Weng, Mingxi Jia, George Konidaris, Stefanie Tellex 3/16/2026

Accelerating Residual Reinforcement Learning with Uncertainty Estimation

Proposes uncertainty estimation improvements to Residual Reinforcement Learning for faster adaptation of pretrained policies with sparse rewards.

Ax Rui Huang, Shitong Shao, Zikai Zhou, Pukun Zhao, Hangyu Guo, Tian Ye, Lichen Bai, Shuo Yang, Zeke Xie 3/16/2026

Accelerating Diffusion Model Training under Minimal Budgets: A Condensation-Based Perspective

Data condensation approach for training diffusion models with minimal computational budget by constructing smaller synthetic training datasets.

Ax Tianyin Liao, Ziwei Zhang, Yufei Sun, Chunyu Hu, Jianxin Li 3/16/2026

Invariant Graph Transformer for Out-of-Distribution Generalization

Graph transformer architecture designed for invariant learning to improve out-of-distribution generalization on graph-structured data.

Ax Sibylle Marcotte, Gabriel Peyr\'e, R\'emi Gribonval 3/16/2026

Intrinsic training dynamics of deep neural networks

Theoretical study of implicit bias in deep neural network training showing gradient flow induces learning of lower-dimensional parameter structures.

Ax Gyutae Oh, Jitae Shin 3/16/2026

UniPrompt-CL: Sustainable Continual Learning in Medical AI with Unified Prompt Pools

Continual learning framework with unified prompt pools for medical imaging tasks, addressing domain-specific challenges in adaptive AI.

Ax Arwen Bradley 3/16/2026

Local Mechanisms of Compositional Generalization in Conditional Diffusion

Analysis of compositional generalization mechanisms in conditional diffusion models, studying length generalization on controlled image generation tasks.

Ax Abhishek Moturu, Muhammad Muzammil, Anna Goldenberg, Babak Taati 3/16/2026

LiLAW: Lightweight Learnable Adaptive Weighting to Meta-Learn Sample Difficulty, Improve Noisy Training, Increase Fairness, and Effectively Use Synthetic Data

Lightweight meta-learning method using three parameters to dynamically adjust sample loss weights for noisy training, fairness, and synthetic data utilization.

Ax Krishu K Thapa, Reet Barik, Krishna Teja Chitty-Venkata, Murali Emani, Venkatram Vishwanath 3/16/2026

PreLoRA: Hybrid Pre-training of Vision Transformers with Full Training and Low-Rank Adapters

Hybrid pre-training approach using low-rank adapters alongside full training to reduce computational cost for vision transformer training.