Fixed-Set Robustness in Programming by Example: Example Corruption and Semantic Partition Recovery
arXiv:2607.01280v1 Announce Type: new
Abstract: Programming-by-example systems infer programs from a small set of input-output examples. Robust PBE work usually models wrong examples as samples from a stochastic noise process and then minimizes an expected or empirical loss. This paper studies a di...
Domain Knowledge Based Temporal-Spatial Graph Convolution Network for ECG Recognition
arXiv:2607.01282v1 Announce Type: new
Abstract: In light of strides in Arti cial Intelligence (AI) and its wide spread application, challenges persist in the interpretability of AI models, particularly within specialized domains like healthcare, such as electro cardiograph (ECG) recognition. Rather...
PACE: A Neuro-Symbolic Framework for Plausible and Actionable Counterfactual Explanations
arXiv:2607.01306v1 Announce Type: new
Abstract: Counterfactual explanations explain machine learning predictions by identifying minimal input changes that would alter a model's decision. Although many existing methods successfully generate prediction-changing alternatives, they often produce unreal...
Auto-FL-Research: Agentic Search for Federated Learning Algorithms
arXiv:2607.01366v1 Announce Type: new
Abstract: Federated learning (FL) research often depends on many small but consequential algorithmic choices: optimizer variants, server aggregation rules, local training schedules, normalization, regularization, and model architecture. These choices are expens...
The Wiola Architecture for Efficient Small Language Models
arXiv:2607.01394v1 Announce Type: new
Abstract: We present Wiola, a fully original Small Language Model (SLM) architecture built from first principles, sharing no structural lineage with any existing model family including GPT, LLaMA, Mistral, or Falcon. Wiola introduces five independently novel co...
Agent4cs: A Multi-agent System for Code Summarization in Large Hierarchical Codebases
arXiv:2607.01425v1 Announce Type: new
Abstract: Understanding large, complex codebases, especially those with obfuscated structures and incomplete documentation, remains a significant challenge. Existing code summarization solutions often rely on a single language model or coding assistant like Cla...
When Should Service Agents Reconsider? Difficulty-Routed Control in Customer-Service Operations
arXiv:2607.01426v1 Announce Type: new
Abstract: Autonomous customer-service agents are shifting from conversational interfaces toward operational execution roles: they retrieve firm records, apply service policies, and execute backend writes such as refunds, cancellations, exchanges, order modifica...
Interfaze Ships diffusion-gemma-asr-small, an Open-Source Diffusion ASR Model Transcribing Six Languages via DiffusionGemma’s Parallel Denoising Decoder
Interfaze open-sourced diffusion-gemma-asr-small, a multilingual ASR model that transcribes via diffusion, not autoregression. It adds audio to Google's frozen DiffusionGemma using a ~42M-parameter adapter. One adapter covers six languages, with transcription cost set by denoising steps, not transcr...
Meet Alibaba’s Page Agent: A JavaScript In-Page GUI Agent That Controls Web Interfaces With Natural Language Through the DOM
Alibaba's Page Agent runs as client-side JavaScript inside the webpage. It reads the live DOM as text, then clicks and types from natural-language commands. No screenshots, no multimodal model, and no backend rewrite are required.
The post Meet Alibaba’s Page Agent: A JavaScript In-Page GUI Agent Th...
Frameworks like Lean Six Sigma and business process management (BPM) first gained traction because they promised clarity in the chaos—a structured way to bring order to messy, sprawling operations. Lean Six Sigma emphasized statistical rigor and quality control; BPM created end-to-end maps of how wo...
OpenAI proposed donating 5% of its equity to a US sovereign wealth fund
OpenAI CEO Sam Altman has reportedly proposed giving 5% of the company’s equity to a U.S. sovereign wealth fund, reviving discussions about letting the public share in the financial gains from the AI boom.
LangGraph, CrewAI, OpenAI Agents SDK, Google ADK, Mastra, and more. If you're building AI agents in 2026, these are the frameworks worth paying attention to before starting your next project.
t0-alpha is a decoder-style patch transformer for probabilistic time-series forecasting. Raw series are split into 32-step patches, embedded, processed through causal time-attention and group-attention layers, and decoded into future quantiles rather than a single point forecast.
The post Time-Serie...
Artificial intelligence may have captured the public imagination through chatbots and image generators, but some of its most consequential use cases are unfolding far from consumer-facing tools. In industries where physical infrastructure, operational continuity, and safety are paramount, AI is beco...
Building the foundation for an autonomous enterprise
Artificial intelligence may have captured the public imagination through chatbots and image generators, but some of its most consequential use cases are unfolding far from consumer-facing tools. In industries where physical infrastructure, operational continuity, and safety are paramount, AI is beco...
The Google Health API Got a CLI: ghealth is an Open-Source Tool for Your Fitbit Air Data
The Google Health API now has an open-source CLI. ghealth is a single Go binary that exposes 40 data types as agent-ready JSON. It is a community project, not an official Google release. Here's how it works, and what to check before granting OAuth access.
The post The Google Health API Got a CLI: gh...
Representation as a Bottleneck for Mechanistic Interpretability: The Manifestation Unit Protocol
arXiv:2607.00089v1 Announce Type: new
Abstract: Mechanistic interpretability has produced a rich inventory of component-level analyses that characterise what neural-network components encode and how they interact. Their outputs, however, are not easily reusable: selectivity tables, circuit diagrams...
SNAP-FM: Sparse Nonlinear Accelerated Projection for Physics-Constrained Generative Modeling
arXiv:2607.00095v1 Announce Type: new
Abstract: Generative models have emerged as scalable surrogates for physical simulation, yet they offer no guarantee that their outputs respect the conservation laws, boundary conditions, and nonlinear invariants that govern the underlying physics. Constrained ...
A Filtered Mixture-of-Generators for Fully Synthetic Survival Training
arXiv:2607.00127v1 Announce Type: new
Abstract: Survival analysis models time-to-event data, but in clinical settings training data are costly and scarce: events accrue over years of follow-up, cohorts are small, and privacy regulations restrict sharing across institutions. Tabular generative model...
GRPO, Dr. GRPO, and DAPO Are Three Operations on One Number: The Group-Standard-Deviation Identity
arXiv:2607.00152v1 Announce Type: new
Abstract: Three of the most popular methods for training language models to reason look like three different tricks. They are not. All three adjust a single number: standard deviation, reflecting how much a prompt's sampled answers disagree. When such a model i...