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How Much Do LLM-as-a-Judge Design Choices Matter? A Systematic Comparison of Prompt Designs, Rating Scales, and Models

arXiv:2610.05094v1 Announce Type: cross Abstract: Researchers increasingly use Large Language Models as judges (LLM-as-a-judge) to evaluate model outputs. Yet there are no standards for how to design

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How Much Evidence Should a Coding Agent's Self-Correction Carry? Adaptive Dirichlet Evidence for Self-Distillation

DGX agent

arXiv:2610.08514v1 Announce Type: new Abstract: Execution feedback lets coding agents revise programs and learn from their own corrections. A correction's learning weight should reflect both the trans

model-releasesarxiv-cs-ai

7 Oct 2026

How much of AutoResearch is research, and how much is search?[D]

I've recently been working part-time on an AutoResearch-style project. The setup is roughly: humans take recent work from top-tier ML/AI conferences, turn part of it into a well-defined task with an e

agentsr-machinelearning

How Much Planning Is Enough? Reducing Search and Computation in World-Model Planning

arXiv:2610.08350v1 Announce Type: cross Abstract: Visual world models enable goal-directed control through decision-time action search, but their deployment efficiency is often limited by conservative

How Qlik built grounded, enterprise-scale AI with Amazon Bedrock

Qlik built Qlik Answers on Amazon Bedrock to give its 40,000+ customers grounded, sourced answers across structured and unstructured enterprise data. Learn how a layered, multi-agent architecture with

agentsaws-ml-blog

How Well Do LLMs Reason with Noisy Evidence? An Active Visual Reasoning Benchmark

model-releasesarxiv-cs-ai

arXiv:2610.07751v1 Announce Type: new Abstract: Real-world reasoning rarely reduces to static question answering: agents must actively gather information from tools and sensors that are often noisy an

Hardware

https://www.together.ai/blog/expanding-our-enterprise-inference-capacity-with-ibm-cloud-and-nvidia

Together AI announced that it is expanding its enterprise‑grade inference capabilities by partnering with IBM Cloud and NVIDIA. The move leverages IBM’s cloud platform for scalable compute resources w

hardwaretogether-ai--x

Industry

https://x.com/nithinaray/status/2107848358132142280

industrycristobal-valenzuela--x

Ben Affleck reveals he writes Python, understands convolutional neural networks, worked extensively with GPUs, and used his celebrity status to get private looks at Google and OpenAI’s video models “I

Hub for Outliers, Spokes for Inliers: Uniform Latent Space Construction for Dual-Mismatched Semi-Supervised Learning

arXiv:2610.07610v1 Announce Type: new Abstract: Semi-supervised learning typically assumes that labeled and unlabeled data share an identical class distribution and label space. However, this setting

researcharxiv-cs-lg

HuC-VideoMAE: Human-Centric Video Masked Autoencoding from synthetic data

arXiv:2610.08433v1 Announce Type: new Abstract: Modern action recognition models rely on video transformers pretrained on massive collections of web-crawled videos, such as Kinetics-700. However, the

researcharxiv-cs-cv

Humanoid Horizon: Extending Task Horizon in Whole-Body Loco-Manipulation via Parallel Training, Dynamic Starting, and Reward Gating

model-releasesarxiv-cs-ro

arXiv:2610.08320v1 Announce Type: new Abstract: Cluttered indoor environments, where large and heavy objects are scattered across diverse surfaces, require humanoid robots to sequentially navigate, gr

Hybrid Cross-Modal Attention Network for Early Breast Cancer Detection in Low-Resource Clinical Settings

arXiv:2610.07243v1 Announce Type: new Abstract: Breast cancer is the leading cause of cancer-related mortality among women in Sub-Saharan Africa, where delayed diagnosis results from limited radiology

local-aiarxiv-cs-cv

Hardware

Hybrid Latent Attention for Looped Language Models

arXiv:2610.07940v1 Announce Type: cross Abstract: Looped language models apply the same stack of layers T times to each token, which deepens the model without adding parameters but multiplies its key-

hardwarearxiv-cs-ai

HygieneRoboBench: Benchmarking Hygiene-Aware Planning for Household Robots

arXiv:2610.08642v1 Announce Type: cross Abstract: Contact with contaminated objects can spread hazards through a household robot's grippers, tools, and shared surfaces, while new contacts can make an

Hypergraph-Enhanced Dual Convolutional Network for Bundle Recommendation

arXiv:2312.11018v3 Announce Type: replace-cross Abstract: Bundle recommendation ranks sets of related items rather than isolated items. Its central challenge is to connect user preferences, item inter

Applications

HyperNSDE: Personalized Neural SDEs for Joint Static-Longitudinal Clinical Data Generation

arXiv:2610.07383v1 Announce Type: cross Abstract: Synthetic patient data generation is a promising solution to the dual challenge of data scarcity and privacy constraints in healthcare machine learnin

applicationsarxiv-cs-lg

I re-trained the DFlash 2 drafter for Ternary Bonsai 2 27B: 2.2x on an L4 (3.2x on code edits with ngram lookup), 1.5x on a Mac, 1.2x in Chrome

model-releasesr-localllama

PrismML's Ternary Bonsai 2 27B fits a 24 GB card or Mac, but decodes at ~30 tok/s on an L4 and ~21 on an M4 Pro. z-lab's DFlash 2 drafter was trained on bf16 Qwen3.8-27B, so it guesses worse on the te

I released an LLM plugin for sending prompts to OpenAI's new Jev-clone decision model that's based on GPT-6 Luna https://simonwillison.net/2…

model-releasessimon-willison--x

Simon Willison released the **“llm-openai-decisions”** plugin (version 0.1a0) on October 7 , 2026. The lightweight library lets developers send prompts directly to OpenAI’s new Jev‑clone decision mode

IdeaAnchor: Teaching LLMs to Turn Literature into Research Ideas

arXiv:2610.08781v1 Announce Type: cross Abstract: Scientific research often begins by synthesizing ideas from a set of related papers to identify gaps and formulate new directions. However, training l

Idea/Thinking outloud: Minimax to build LoRA datasets?

local-air-stablediffusion

Since Minimax H3 does such a good job of taking a source or two of a character and doing an animation with them while maintaining the character's integrity, it has me thinking that it could be used to

Identifiability Analysis of Linear ODE Systems with Hidden Confounders

arXiv:2410.21917v3 Announce Type: replace-cross Abstract: The identifiability analysis of linear Ordinary Differential Equation (ODE) systems is a necessary prerequisite for making reliable causal inf

researcharxiv-cs-lg

Identifiable World Models from Pretrained Diffusion Representations

arXiv:2610.07028v1 Announce Type: new Abstract: Diffusion-based world models can generate and predict trajectories in high-dimensional dynamical systems, but predictive accuracy does not imply that th

safetyarxiv-cs-lg

Identifying Introspection From the Inside

arXiv:2610.07186v1 Announce Type: new Abstract: Large language models make claims about themselves that are both consequential and increasingly difficult to verify from behavior alone. How can we dist

Identity-Conditioned Score Fusion for Open-Set Person Re-Identification

model-releasesarxiv-cs-cv

arXiv:2610.07366v1 Announce Type: new Abstract: Robust person re-identification often combines complementary cues such as face, gait, and body shape. While adaptive fusion typically targets query qual

Tutorials

IEEE 802.11bx - WLAN Intelligent Networking (WIN): Toward an AI-Ready Wi-Fi 9

arXiv:2610.07900v1 Announce Type: cross Abstract: Wi-Fi 9 is expected to go beyond mere communication and provide new services such as sensing or computation. At this juncture, Artificial Intelligence

tutorialsarxiv-cs-ai

If you need any more evidence about how exciting local AI (and llamacpp) is! From the @Microsoft windows launch today with @satyanadella @sr…

On October 7, 2026, Clement Delangue noted that Microsoft’s Windows launch—highlighted by Satya Nadella and others—demonstrated the growing excitement around local AI solutions such as llamacpp. The e

local-aiclem-delangue--x

iGPC: Generative Motion Priors for Object-Aware Humanoid Interaction

arXiv:2610.08120v1 Announce Type: new Abstract: Humanoid robots operating in unstructured environments must combine robust whole-body control with the ability to perceive and physically interact with

safetyarxiv-cs-ro

Illusory Pattern Perception Drives Spurious Inference in Large Language Models

arXiv:2610.07791v1 Announce Type: new Abstract: Illusory pattern perception is a well-documented human cognitive tendency to infer meaningful relationships in data that is actually random. Such a tend

Image Bitstream Fine-grained Understanding for Privacy-Friendly AIoT

model-releasesarxiv-cs-cv

arXiv:2610.08414v1 Announce Type: new Abstract: Image Bitstream Fine-grained Understanding (IBFU) aims to directly perform fine-grained classification and semantic description generation from encoded

Image-Space Refraction Correction for Underwater 3D Reconstruction: Warping Flat-Port Views into Pinhole Perspective

arXiv:2610.07788v1 Announce Type: new Abstract: Consumer-grade cameras in flat-port housings are widely used for underwater exploration and mapping of coral reefs and seafloor habitats due to their lo

researcharxiv-cs-cv

Image-text retrieval with EmbeddingGemma 2's vision tower, running in the browser on WebGPU

EmbeddingGemma 2 came out this week. It maps images and text into one 768-dim space, so you can search photos by describing them. I ported its text and vision towers to ruNNtime, a WebGPU inference li

local-air-localllama

ImpactMat: Continuous Material Estimation for Inverse Impact Sound Rendering

model-releasesarxiv-cs-lg

arXiv:2610.07061v1 Announce Type: cross Abstract: Impact sound rendering synthesizes the sound produced when a 3D object is struck, but practical renderers often rely on fixed material presets such as

Improving Diversity in LLM Short Story Generation

arXiv:2610.06729v2 Announce Type: replace Abstract: Large language models (LLMs) can generate accurate responses, but these are void of diversity. We attempt to address this for the task of creative s

Improving Mixup Calibration with Wasserstein Distributionally Robust Optimization

model-releasesarxiv-cs-cv

arXiv:2506.17874v3 Announce Type: replace-cross Abstract: In many real-world applications, ensuring the robustness and stability of deep neural networks (DNNs) is crucial, particularly for image class

Improving Synthetic Data Generation for Argument Mining via Adversarial Reinforcement Learning

model-releasesarxiv-cs-cl

arXiv:2610.07699v1 Announce Type: cross Abstract: Argument Mining (AM) is fundamentally constrained by the scarcity of high-quality structure-annotated datasets. While LLMs have shown promise in synth

In agentic search, a GPT-OSS-120B agent using the 9B model answers 64.0% of BrowseComp+ questions correctly, 4.9 points ahead of the next Co…

In agentic search, a GPT‑OSS‑120B agent employing the 9B model achieves a 64.0 % accuracy on BrowseComp+ questions. This performance is 4.9 points higher than the next best ColBERT model and requires

agentsperplexity--x

in the meantime if you need consistently high document parsing quality across every dimension, come check out llamaparse: https://cloud.llam…

On October 7, 2026 Jerry Liu tweeted that “llamaparse” delivers consistently high document‑parsing quality across every dimension. The service can be accessed through cloud.llamaindex.ai. His post cur

agentsjerry-liu--x

Applications

In With the Old: Enhancing 'Classical' Document Automation with Generative AI

arXiv:2610.07480v1 Announce Type: new Abstract: Software-based legal assistance systems have leveraged many different forms of knowledge representation and reasoning. This article explores how documen

applicationsarxiv-cs-ai

Incidental information contaminates patient notes and disrupts clinical reasoning in large language models

arXiv:2610.08585v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly relied upon to support ambient documentation and clinical reasoning. Here we examine the impact of a failu

Independent Multi-Agent Reinforcement Learning with Counterfactual Semantic-Social World Models

model-releasesarxiv-cs-lg

arXiv:2610.07704v1 Announce Type: cross Abstract: Fully decentralized multi-agent reinforcement learning (MARL), also referred to as independent learning, requires each agent to learn and act using on

Inductive Claims Extraction at Scale

arXiv:2610.05275v2 Announce Type: replace Abstract: A large part of political discourse on social media is built and expressed at a level of claims: i.e. declarative, typically single-clause statement

Inference and learning in sparse autoencoders as natural gradient flow

arXiv:2610.07389v1 Announce Type: cross Abstract: Sparse autoencoders are widely used to uncover interpretable features in neural networks, yet reliable recovery remains difficult when features overla

Inference-Time Projection for Physically Valid Biomolecular Diffusion Models

arXiv:2610.07037v1 Announce Type: new Abstract: AlphaFold 3-style cofolding models predict biomolecular complexes with high structural accuracy, yet a large fraction of their outputs are physically in

local-aiarxiv-cs-ai

Infor uses industry-specific AI to address agent hallucinations

Industry-specific AI brings business context to agents handling enterprise workflows. Building around industry processes can help companies address reliability concerns as they automate more tasks. In

agentssiliconangle

Information-Dense Synthesis for Molecular Discovery

arXiv:2610.08495v1 Announce Type: cross Abstract: Machine learning can accelerate molecular discovery by designing molecules and planning experiments. However, many scientific challenges demand molecu

researcharxiv-cs-lg

Applications

InStyle: Instant Appearance Stylization of 3D Shapes

arXiv:2512.03683v2 Announce Type: replace Abstract: 3D stylization is central to game development, virtual reality, and digital arts, where the demand for diverse assets calls for scalable methods tha

applicationsarxiv-cs-cv

InterCorrect: Intersection-Aware Correction of Demographic Model Merging for Fair ASR

arXiv:2610.08604v1 Announce Type: new Abstract: Automatic Speech Recognition (ASR) systems often show uneven performance across demographic groups, and errors can be especially difficult to address fo

Interleaved Projected Gradient Descent for Safe Imitation Learning

arXiv:2610.07167v1 Announce Type: cross Abstract: We propose an imitation-learning design for neural-network control policies under state and input constraints. Training alternates a standard imitatio

safetyarxiv-cs-lg