Search: “inference”

Toward Generalizable Deep Learning Based Peatland Fire Detection via Walsh Hadamard Transform and Domain Adaptation

arXiv:2603.02465v2 Announce Type: replace-cross Abstract: Machine learning-based wildfire detection has advanced significantly using deep learning models trained on large wildfire image and video data

researcharxiv-cs-ai

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Tracing the Latent Threads: A Mechanistic Study of How LLMs Represent and Operationalize Race and Ethnicity Cues

DGX agent

arXiv:2601.12868v2 Announce Type: replace Abstract: Large language models (LLMs) increasingly operate in high-stakes settings where demographic attributes such as race and ethnicity may be explicitly

safetyarxiv-cs-cl

1 Sept 2026

Transformer-Encoder Trees for Efficient Multilingual Machine Translation and Speech Translation

model-releasesarxiv-cs-ai

arXiv:2509.17930v3 Announce Type: replace-cross Abstract: Multilingual translation suffers from computational redundancy, especially when translating into multiple languages simultaneously. In additio

Update: llama.cpp for Radeon VII / MI50 / MI60 — +14% PP, +9% long-context fill vs upstream + adaptive Flash Attention

I posted a new gfx906 based llama.cpp fork a few days ago. One of the main points of critique was that i did not provide sufficient numbers for the gains to be achieved. -- TL;DR: After switching our

Which current local models that can run within 128GB generate the best SVG pelicans?

I used a famous Simon Willison's pelican riding a bicycle prompt on the biggest local LLMs that can run on 128GB Apple Silicon. U used quantizations by Unsloth. Qwen3.8 Flash-Next gives a lot of detai

A comprehensive and trustworthy benchmark of AI methods for change detection in Earth observation

model-releasesarxiv-cs-cv

arXiv:2608.28247v1 Announce Type: new Abstract: Change detection in Earth observation (EO) is critical for monitoring land surface transformations, yet recent research in the field is constrained by i

AIM: Anchor Identity Features, Then Match for Multimodal Large Language Model Unlearning

arXiv:2608.28312v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) can memorize identity-specific facts about people in their fine-tuning data, creating privacy risks when a pe

Are These Modules Worth Their Cost? A Paradigm-Level Accuracy-Cost Analysis of In-context Learning Text-to-SQL

arXiv:2608.28432v1 Announce Type: new Abstract: Recent advances in in-context learning (ICL) text-to-SQL have substantially improved execution accuracy on public benchmarks by assembling increasingly

D-TAIA: Domain-Aware LLM Adaptation for Multi-Task Predictive Process Monitoring

arXiv:2608.28236v1 Announce Type: new Abstract: Predictive Process Monitoring (PPM) enables organizations to forecast future process behavior, such as the next activity and remaining time of ongoing c

Safety

Dynamic Alignment Compensation for Hallucination Mitigation in Large Vision-Language Models

arXiv:2608.28058v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs) remain prone to hallucinations, producing responses that are irrelevant or inconsistent with the multimodal input.

safetyarxiv-cs-cv

Safety

From Perspective to Fisheye Depth Estimation and Open-Vocabulary Segmentation

arXiv:2608.27860v1 Announce Type: new Abstract: Vision foundation models are capable of generalizing across 3-dimensional (3D) scenes with high-fidelity estimates; their empirical success can be attri

safetyarxiv-cs-cv

Generalized Splines and Gaussian Processes

arXiv:2608.28446v1 Announce Type: cross Abstract: For finite-dimensional linear inverse problems where the variables are Gaussian, it is well-known that the minimum-mean-square error estimator takes t

I am the product lead for the training platform at @FireworksAI_HQ . Today the Training API and Fireworks Lab are GA. I won’t walk you throu…

model-releasesfireworks-ai--x

I am the product lead for the training platform at @FireworksAI_HQ . Today the Training API and Fireworks Lab are GA. I won’t walk you through all the features. I want to tell you why teams train with

Improved off-policy training of diffusion samplers

arXiv:2402.05098v5 Announce Type: replace Abstract: We study the problem of training diffusion models to sample from a distribution with a given unnormalized density or energy function. We benchmark s

Node-wise Feature Encoding for Neural Performance Prediction

arXiv:2608.27794v1 Announce Type: new Abstract: As neural networks are increasingly deployed on resource constrained edge devices, accurate prediction of latency and energy is critical for efficient n

Real-Time Musculoskeletal Surrogates for Pediatric Cerebral Palsy: a Credibility Pilot

arXiv:2608.28371v1 Announce Type: new Abstract: Real-time musculoskeletal (MSK) surrogates could support personalized rehabilitation for children with cerebral palsy (CP), but their credibility depend

researcharxiv-cs-cv

Roleplaying with Structure: Synthetic Therapist-Client Conversation Generation from Questionnaires

arXiv:2510.25384v2 Announce Type: replace Abstract: Large Language Models (LLMs) are promising tools for synthetic data generation in mental health. However, privacy policies and restrictions forced p

Tutorials

SCALE: Self-uncertainty Conditioned Adaptive Looking and Execution for Vision-Language-Action Models

arXiv:2602.04208v3 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models have emerged as a promising paradigm for general-purpose robotic control, with test-time scaling (TTS) gai

tutorialsarxiv-cs-lg

Simplex-to-Euclidean Bijection for Conjugate and Calibrated Multiclass Gaussian Process Classification

arXiv:2603.16621v2 Announce Type: replace Abstract: We propose a conjugate and calibrated Gaussian process (GP) model for multi-class classification by exploiting the geometry of the probability simpl

applicationsarxiv-cs-lg

Hardware

SOMTab: Set-Order Mamba for Efficient Tabular In-Context Learning

arXiv:2608.27882v1 Announce Type: new Abstract: Tabular foundation models based on in-context learning have recently emerged as strong alternatives to task-specific model fitting. However, the current

hardwarearxiv-cs-lg

Spectral Query-Key Product Weight Steering for Training-Free VLM Hallucination Mitigation

arXiv:2606.20419v2 Announce Type: replace Abstract: Vision-language models (VLMs) often generate fluent but visually unsupported descriptions, especially by mentioning objects absent from the image. W

local-aiarxiv-cs-cv

Agents

VICT: Verifier-Instrumented Credit Tracing for Long-Horizon LLM Agent Reinforcement Learning

arXiv:2608.28128v1 Announce Type: new Abstract: Fine-grained credit assignment is a central challenge in reinforcement learning for long horizon LLM agents. Standard objectives often train from progra

agentsarxiv-cs-lg

Why Didn't It Check? Unsupported Final Claims and Their Repair in Two Tool-Equipped Language Models

model-releasesarxiv-cs-cl

arXiv:2608.27768v1 Announce Type: cross Abstract: A language model with access to tools can commit to a final claim unsupported by the evidence it has seen, even when a single available tool call woul

Qwen3.8-27B thinking xhigh Vs. thinking off - Apple M5 Max

I ran a few benchmarks on my MacBook Pro M5 Max with oMLX: Running Qwen3.8-27B with thinking off has a big effect on output quality. Running it with thinking on xhigh burns 5.5x the tokens and runs 6x

29 Aug 2026

use llms to auto annotation your dataset locally

hi i make tool for this called llmog it's purpose to make llms free to - auto annotation datasets - reclassification existing yolo datasets running totally local using llama cpp or vllm or use externa

29 Aug 2026

Andreessen Horowitz raises $1.1B AI infrastructure fund for chips, robots and more

Andreessen Horowitz today announced that it has raised a 1.1 billion fund to back artificial intelligence infrastructure startups. The Machine Age Fund will invest in companies that make data center e

local-aisiliconangle

CLAP: Cross-Embodiment Video World Models are Zero-Shot Physical Simulators

arXiv:2608.27406v1 Announce Type: cross Abstract: State-of-the-art action-conditioned video models are typically restricted to a single robot embodiment, preventing them from leveraging the vast corpu

applicationsarxiv-cs-ai

Classical and Hybrid Quantum Machine Learning for Trigger-Like Event Selection on CMS Open Data: An Eight-Qubit, PCA-Constrained Benchmark

arXiv:2608.26224v1 Announce Type: cross Abstract: Event triggering sits at the heart of high-energy physics, where the rare events of interest must be retained while an overwhelming background is disc

Compositional Generalization via Structural Identification in a Category-Theoretic Framework

arXiv:2608.26465v1 Announce Type: new Abstract: Compositional generalization is usually evaluated through model accuracy. We instead ask which structural or lexical identifications make held-out COGS

Diagnosing Conformal Prediction Failures Under Distribution Shift: A COVID-19 Case Study

arXiv:2601.00908v2 Announce Type: replace-cross Abstract: Conformal prediction provides distribution-free coverage guarantees, but these degrade under distribution shift - and practitioners lack tools

applicationsarxiv-cs-ai

Discovering Relationships in Data Lakes Using Large Language Models: An Industrial Case

arXiv:2608.26750v1 Announce Type: new Abstract: Data lakes rely on metadata to remain usable, yet this meta data is often limited or weakly informative for column relationship discovery, especially in

researcharxiv-cs-ai

Agents

Do Language Models Follow Occam's Razor? An Evaluation of Parsimony in Inductive and Abductive Reasoning

arXiv:2509.03345v3 Announce Type: replace Abstract: Non-deductive reasoning, encompassing inductive and abductive reasoning, is essential in addressing complex real-world questions. One key feature of

agentsarxiv-cs-ai

Safety

Evaluating AI Generated Summaries for Cancer Patients

arXiv:2608.26154v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly being integrated into digital health platforms to generate summaries of complex medical data. Although t

safetyarxiv-cs-ai

Fairness Invariants: A Relational Approach to Explaining and Mitigating Fairness Bugs

arXiv:2608.26209v1 Announce Type: cross Abstract: Data-driven software systems are increasingly deployed in high-stakes socio-economic domains, from criminal justice to financial lending. However, the

local-aiarxiv-cs-ai

Agents

Finding the Right Evidence: Factor-Guided Coarse-to-Fine Reasoning for Long Videos

arXiv:2608.26355v1 Announce Type: new Abstract: While LVLMs rapidly improve, long-video question answering still remains challenging: relevant evidence is sparse, and question-relevant context often f

agentsarxiv-cs-cv

GSM8K-V: Can Vision Language Models Solve Grade School Math Word Problems in Visual Contexts

model-releasesarxiv-cs-ai

arXiv:2509.25160v2 Announce Type: replace-cross Abstract: Mathematical reasoning is a key capability for vision-language models (VLMs), yet current benchmarks mainly evaluate text-based or explicitly

hoBIT: A Profile-Aware Retrieval-Augmented Chatbot for University Academic Advising

arXiv:2608.26604v1 Announce Type: cross Abstract: In university academic advising, identical questions can require different answers depending on a student's department, admission cohort, and degree p

Multivariate Diffusion Transformer with Decoupled Attention for High-Fidelity Mask-Text Collaborative Facial Generation

arXiv:2511.12631v3 Announce Type: replace-cross Abstract: While significant progress has been achieved in multimodal facial generation using semantic masks and textual descriptions, conventional featu

researcharxiv-cs-ai

Neural Regression with Embeddings for Numerical Attribute Prediction in Knowledge Graphs

arXiv:2608.26729v1 Announce Type: new Abstract: In recent years, transductive knowledge graph embedding models have been applied to tasks such as link prediction and query answering. Although knowledg

applicationsarxiv-cs-lg

On the Indistinguishability of Human v/s AI Generated Text

arXiv:2608.26797v1 Announce Type: new Abstract: The rapid improvement of LLMs has made distinguishing AI-generated text from human writing a pressing problem. This challenge is further amplified by pa

RubricRM: Generative Reward Modeling via Dynamic Rubrics for Image Generation and Editing

arXiv:2608.26956v1 Announce Type: new Abstract: Reward models play an essential role in aligning visual generative models, yet most existing visual reward models use a single scalar score or rely on f

researcharxiv-cs-cv

Self-Augmented Diffusion Guidance for Physics-Informed Generation

arXiv:2608.26748v1 Announce Type: new Abstract: Diffusion models can be used to generate spatiotemporal signals of physical phenomena, such as time-series images of fluid dynamics. However, a major li

Sharp Minimax Regret for Infinite-Memory Logistic Prediction

arXiv:2608.26515v1 Announce Type: cross Abstract: We study online prediction for a specific finite-alphabet, exogenously driven source with infinite input memory. Independent Rademacher inputs (U_t) a

local-aiarxiv-cs-lg

Simple Actors and Deep Critics for Scalable Reinforcement Learning

arXiv:2608.26659v1 Announce Type: new Abstract: Recent progress in offline reinforcement learning (RL) has been driven by expressive generative actors such as diffusion and flow-matching policies, whi

SLM-Conditioned Hierarchical Relation Routing for Labeled Property Graph Learning

model-releasesarxiv-cs-cl

arXiv:2608.26132v1 Announce Type: cross Abstract: Labeled property graphs combine relational structure with heterogeneous textual and categorical properties attached to both nodes and relationships. C

Temporally-Grounded Language Generation: Towards Real-Time Vision-Language Models

model-releasesarxiv-cs-ai

arXiv:2505.11326v2 Announce Type: replace-cross Abstract: Vision-language models (VLMs) have shown remarkable progress in offline tasks such as image captioning and video question answering. However,

The Accuracy-Efficiency Paradox Quantifying Net Energy Loss in on-Device Energy Forecasting

arXiv:2608.26134v1 Announce Type: new Abstract: Energy forecasting aims to maximize accuracy to ensure energy efficiency by reducing energy waste, an objective that applies equally to on-device foreca

local-aiarxiv-cs-ai

Vision-centric generative AI models: A software-hardware perspective

model-releasesarxiv-cs-cv

arXiv:2608.27199v1 Announce Type: new Abstract: Vision generative artificial intelligence (AI) has emerged as one of the most rapidly advancing areas of deep learning. The explosion of multimodal mode