Search: “applications”

MuTSE: A Human-in-the-Loop Multi-use Text Simplification Evaluator

arXiv:2604.08947v1 Announce Type: cross Abstract: As Large Language Models (LLMs) become increasingly prevalent in text simplification, systematically evaluating their outputs across diverse prompting

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[N] AMA Announcement: Max Welling (VAEs, GNNs, AI4Science & CuspAI)

DGX agent

This r/MachineLearning AMA announcement features Max Welling, a prominent figure in machine learning renowned for his foundational contributions to probabilistic deep learning, including the co-develo

researchr-machinelearning

13 Apr 2026

Offline Local Search for Online Stochastic Bandits

arXiv:2604.09423v1 Announce Type: new Abstract: Combinatorial multi-armed bandits provide a fundamental online decision-making environment where a decision-maker interacts with an environment across T

On Divergence Measures for Training GFlowNets

arXiv:2410.09355v2 Announce Type: cross Abstract: Generative Flow Networks (GFlowNets) are amortized inference models designed to sample from unnormalized distributions over composable objects, with a

Physics-guided surrogate learning enables zero-shot control of turbulent wings

arXiv:2604.09434v1 Announce Type: cross Abstract: Turbulent boundary layers over aerodynamic surfaces are a major source of aircraft drag, yet their control remains challenging due to multiscale dynam

PhysInOne: Visual Physics Learning and Reasoning in One Suite

arXiv:2604.09415v1 Announce Type: cross Abstract: We present PhysInOne, a large-scale synthetic dataset addressing the critical scarcity of physically-grounded training data for AI systems. Unlike exi

PinpointQA: A Dataset and Benchmark for Small Object-Centric Spatial Understanding in Indoor Videos

arXiv:2604.08991v1 Announce Type: cross Abstract: Small object-centric spatial understanding in indoor videos remains a significant challenge for multimodal large language models (MLLMs), despite its

Post-Selection Distributional Model Evaluation

arXiv:2603.23055v2 Announce Type: replace-cross Abstract: Formal model evaluation methods typically certify that a model satisfies a prescribed target key performance indicator (KPI) level. However, i

safetyarxiv-cs-lg

Practical Bayesian Inference for Speech SNNs: Uncertainty and Loss-Landscape Smoothing

arXiv:2604.08624v1 Announce Type: cross Abstract: Spiking Neural Networks (SNNs) are naturally suited for speech processing tasks due to their specific dynamics, which allows them to handle temporal d

PRAGMA: Revolut Foundation Model

arXiv:2604.08649v1 Announce Type: cross Abstract: Modern financial systems generate vast quantities of transactional and event-level data that encode rich economic signals. This paper presents PRAGMA,

researcharxiv-cs-cl

PS-TTS: Phonetic Synchronization in Text-to-Speech for Achieving Natural Automated Dubbing

arXiv:2604.09111v1 Announce Type: cross Abstract: Recently, artificial intelligence-based dubbing technology has advanced, enabling automated dubbing (AD) to convert the source speech of a video into

Reservoir observer enhanced with residual calibration and attention mechanism

arXiv:2604.08592v1 Announce Type: new Abstract: Reservoir observers provide a data-driven approach to the inference of unmeasured variables from observed ones for nonlinear dynamical systems. While pr

Rethinking Prospect Theory for LLMs: Revealing the Instability of Decision-Making under Epistemic Uncertainty

arXiv:2508.08992v3 Announce Type: replace Abstract: Prospect Theory (PT) models human decision-making behaviour under uncertainty, among which linguistic uncertainty is commonly adopted in real-world

Local Ai

Revitalizing Black-Box Interpretability: Actionable Interpretability for LLMs via Proxy Models

arXiv:2505.12509v3 Announce Type: replace-cross Abstract: Post-hoc explanations provide transparency and are essential for guiding model optimization, such as prompt engineering and data sanitation. H

local-aiarxiv-cs-ai

Structured Uncertainty guided Clarification for LLM Agents

arXiv:2511.08798v2 Announce Type: replace-cross Abstract: LLM agents with tool-calling capabilities often fail when user instructions are ambiguous or incomplete, leading to incorrect invocations and

Task-agnostic Low-rank Residual Adaptation for Efficient Federated Continual Fine-Tuning

model-releasesarxiv-cs-lg

arXiv:2505.12318v2 Announce Type: replace Abstract: Federated Parameter-Efficient Fine-Tuning (Fed-PEFT) enables lightweight adaptation of large pre-trained models in federated learning settings by up

Local Ai

Temporal Patch Shuffle (TPS): Leveraging Patch-Level Shuffling to Boost Generalization and Robustness in Time Series Forecasting

arXiv:2604.09067v1 Announce Type: new Abstract: Data augmentation is a crucial technique for improving model generalization and robustness, particularly in deep learning models where training data is

local-aiarxiv-cs-lg

Temporal Transfer Learning for Traffic Optimization with Coarse-grained Advisory Autonomy

arXiv:2312.09436v3 Announce Type: replace-cross Abstract: The recent development of connected and automated vehicle (CAV) technologies has spurred investigations to optimize dense urban traffic to max

The nextAI Solution to the NeurIPS 2023 LLM Efficiency Challenge

model-releasesarxiv-cs-lg

arXiv:2604.09034v1 Announce Type: new Abstract: The rapid evolution of Large Language Models (LLMs) has significantly impacted the field of natural language processing, but their growing complexity ra

this & a hermes agent

Nous Research's Hermes agent framework combines a language model's contextual reasoning capabilities ('this') with an autonomous agent built on their Hermes model series, enabling tool use, multi-step

agentsnous-research--x

Training event-based neural networks with exact gradients via Differentiable ODE Solving in JAX

arXiv:2603.08146v3 Announce Type: replace Abstract: Existing frameworks for gradient-based training of spiking neural networks face a trade-off: discrete-time methods using surrogate gradients support

safetyarxiv-cs-lg

Uncertainty-Aware Transformers: Conformal Prediction for Language Models

arXiv:2604.08885v1 Announce Type: new Abstract: Transformers have had a profound impact on the field of artificial intelligence, especially on large language models and their variants. However, as was

Variational Quantum Physics-Informed Neural Networks for Hydrological PDE-Constrained Learning with Inherent Uncertainty Quantification

arXiv:2604.09374v1 Announce Type: cross Abstract: We propose a Hybrid Quantum-Classical Physics-Informed Neural Network (HQC-PINN) that integrates parameterized variational quantum circuits into the P

Webscale-RL: Automated Data Pipeline for Scaling RL Data to Pretraining Levels

arXiv:2510.06499v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have achieved remarkable success through imitation learning on vast text corpora, but this paradigm creates a tra

when you take agents to production, you need to think about guardrails we provide 2 abstractions for guardrails 1. middleware provides hooks…

when you take agents to production, you need to think about guardrails we provide 2 abstractions for guardrails 1. middleware provides hooks around the agent loop that you can use to handle retries, e

You've Got a Golden Ticket: Improving Generative Robot Policies With A Single Noise Vector

arXiv:2603.15757v2 Announce Type: replace-cross Abstract: What happens when a pretrained generative robot policy is provided a constant initial noise as input, rather than repeatedly sampling it from

@hwchase17 is right, memory creates lock-in. But not just conversations. Tool registries, hooks, agent conventions -> that's harness memory …

@hwchase17 is right, memory creates lock-in. But not just conversations. Tool registries, hooks, agent conventions -> that's harness memory too. In my setup I define agent tools once in a shared regis

I think you should build your own harness too. Build on primitives. Models come and go.

Harrison Chase, co-founder of LangChain, advocates for developers building their own custom harnesses on top of foundational primitives rather than relying on high-level abstractions or specific model

KIV: 1M token context window on a RTX 4070 (12GB VRAM), no retraining, drop-in HuggingFace cache replacement - Works with any model that uses DynamicCache [P]

model-releasesr-machinelearning

KIV is a project shared on r/MachineLearning presenting a drop-in replacement for HuggingFace's `DynamicCache` that enables up to 1 million token context windows on consumer hardware with only 12GB of

Syntheses

Synthesis: Swyx--X

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Auto-generated synthesis of 142 entries about swyx--x

The clarity of this piece by @hwchase17 is immense. No jargon.

Harrison Chase, the creator of LangChain, shared or was referenced in a post praising a piece of writing attributed to him for its clarity and accessibility, notably avoiding technical jargon. The con

The differentiating factor between a prototype and an autonomous system is no longer solely the underlying model weights, but the sophistica…

The differentiating factor between a prototype and an autonomous system is no longer solely the underlying model weights, but the sophistication of the orchestration layer and its capacity for continu

Weekends are for hacking! What are you building with Hermes?

Nous Research posted a weekend community engagement prompt encouraging developers and hobbyists to share what they are building using Hermes, their open-source large language model series. The post re

researchnous-research--x

Just finished reading this blog on agent harnesses. Man, it’s one of the clearest, most practical takes I’ve seen why they’re here to stay a…

Harrison Chase, co-founder of LangChain, shared enthusiasm for a blog post about agent harnesses, describing it as one of the clearest and most practical explanations of why they are a lasting paradig

LangSmith MCP is invisibly underrated One hour to improve an agent from zero observability to 78% cache hit rate - Prompt costs down 70% The…

LangSmith MCP is invisibly underrated One hour to improve an agent from zero observability to 78% cache hit rate - Prompt costs down 70% The single most useful MCP tool for building agents, ever 🔥 htt

Concepts

All People

Auto-generated index of all people mentioned across the wiki.

conceptspeopleindex

We recently identified a security issue involving the third-party developer library Axios that was part of a broader industry incident. We f…

We recently identified a security issue involving the third-party developer library Axios that was part of a broader industry incident. We found no evidence that OpenAI user data was accessed, that ou

model-releasesopenai--x

A-MBER: Affective Memory Benchmark for Emotion Recognition

arXiv:2604.07017v1 Announce Type: new Abstract: AI assistants that interact with users over time need to interpret the user's current emotional state in order to respond appropriately and personally.

A Unified Multi-Layer Framework for Skill Acquisition from Imperfect Human Demonstrations

arXiv:2604.08341v1 Announce Type: new Abstract: Current Human-Robot Interaction (HRI) systems for skill teaching are fragmented, and existing approaches in the literature do not offer a cohesive frame

safetyarxiv-cs-ro

Accelerating data curation with Google Data Cloud

model-releasesgoogle-cloud-ai

In the enterprise landscape, data is often highly fragmented across multiple source systems. Data curation is the process of organizing, cleaning, and enriching raw data to transform it into high-qual

Accelerating innovation and impact across the public sector

model-releasesgoogle-cloud-ai

Leaders across industries around the world are asking: How do we harness all of this powerful technology effectively and at scale, to solve real problems, and drive value and impact, right now?Google

AfriVoices-KE: A Multilingual Speech Dataset for Kenyan Languages

arXiv:2604.08448v1 Announce Type: new Abstract: AfriVoices-KE is a large-scale multilingual speech dataset comprising approximately 3,000 hours of audio across five Kenyan languages: Dholuo, Kikuyu, K

researcharxiv-cs-cl

Agent harnesses are spark LangSmith is databricks

Agent harnesses are spark LangSmith is databricks harnesses seem to be the abstraction that encapsulates all of the 'business logic' or 'business connections' into a coherent unit that you can iterate

AI-Driven Research for Databases

arXiv:2604.06566v1 Announce Type: cross Abstract: As the complexity of modern workloads and hardware increasingly outpaces human research and engineering capacity, existing methods for database perfor

Tutorials

AI fundamentals

OpenAI Academy is a free, publicly accessible learning hub created by OpenAI to democratize AI knowledge, offering tutorials, workshops, and digital content ranging from foundational AI literacy to...

tutorialsopenai

Algebraic Diversity: Group-Theoretic Spectral Estimation from Single Observations

arXiv:2604.03634v2 Announce Type: replace Abstract: We establish that temporal averaging over multiple observations is the degenerate case of algebraic group action with the trivial group G={e}. A

anyways, try out deepagents https://github.com/langchain-ai/deepagents

**deepagents** (github.com/langchain-ai/deepagents) is an open-source, MIT-licensed agent harness built on LangChain and LangGraph, equipped with built-in task planning, a filesystem backend, subag...

As agent systems scale, the control layer becomes the main source of complexity. What starts simple turns into coordination and composition …

As agent systems scale, the control layer becomes the main source of complexity. What starts simple turns into coordination and composition problems. I built langchain-middleware-stack to better struc