Search: “inference”

Reading Between the Lines: Can LLMs Discover the Question Behind the Text?

model-releasesarxiv-cs-cl

arXiv:2609.19070v1 Announce Type: new Abstract: This paper introduces ``question archaeology'', a specific evaluation task focused on inferring the single, authentic 'genesis question' that motivated

17 Sept 2026

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Scaling Articulated Rationales for MLLM-based Recommendation

DGX agent

arXiv:2609.17639v1 Announce Type: cross Abstract: Modern recommendation systems largely infer user preferences from implicit behaviors such as clicks, watch time, and negative feedback, but these sign

applicationsarxiv-cs-ai

17 Sept 2026

Hardware

Technical Report: One-Step Drifting Action Heads for GR00T N1.7

arXiv:2609.18108v1 Announce Type: new Abstract: One-step action generation can substantially reduce the inference cost of vision-language-action (VLA) policies, but its effect on closed-loop task succ

hardwarearxiv-cs-ro

17 Sept 2026

Applications

The future of orchestration: Pine59’s journey to Airflow 3 on Google Cloud

applicationsgoogle-cloud-ai

Operating large data pipelines requires an orchestration layer that scales smoothly as workloads expand. When your pipelines process millions of complex data points every day to feed predictive models

17 Sept 2026

Beta testers wanted (Gemma 4:26b and/or Qwen 3.8:27b)

Anyone interested in trying out a new inference provider? We're testing Gemma 4:26b and Qwen 3.8:27B behind an OpenAI-compatible API and looking for a few users to give them a spin and tell us how it

model-releasesr-ollama

BrainFocus: EEG-Guided ROI Selection for Efficient Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2609.17443v1 Announce Type: new Abstract: Vision-language models (VLMs) achieve strong visual question answering (VQA) performance, but processing large cluttered images is computationally expen

Can We Do Interpretable NLI with Graphs Based on Atomic Propositions?

arXiv:2609.16814v1 Announce Type: new Abstract: While Large Language Model (LLM)-based Natural Language Inference (NLI) systems achieve high accuracy, their decision-making processes lack auditable st

Competence-Preserving Resume Perturbations Expose Presentation Sensitivity in LLM Screening

arXiv:2609.16517v1 Announce Type: cross Abstract: Resume screeners must infer job-relevant competence from resumes whose presentation can vary substantially in wording, structure, stylistic polish, an

CTAN: Cycle-Temporal Attention Network for Embodied Audio-Visual Navigation

arXiv:2609.17420v1 Announce Type: cross Abstract: Audio-visual embodied navigation equips robots with the capability to infer the locations of sound sources by integrating visual inputs and acoustic i

Agents

Distilling Foundation Models for Agentic What-If Reasoning:Cost, Latency, and Governance in a Hybrid LLM+SLM Architecture

arXiv:2609.16091v1 Announce Type: new Abstract: Tabular foundation models deliver strong zero-training predictive performance via in-context learning, but their high inference latency makes them impra

agentsarxiv-cs-lg

FluxVLA Engine: A One-Stop VLA Engineering Platform for Embodied Intelligence

arXiv:2609.17210v1 Announce Type: cross Abstract: Vision-language-action (VLA) models, world-action models (WAMs), and offline reinforcement learning methods are rapidly expanding the design space of

How Humans and LLMs Read Gender into Gender-Neutral Physical Descriptions

arXiv:2609.16366v1 Announce Type: cross Abstract: When foundation models describe people, recent work in AI fairness, accessibility, and ethics recommends avoiding inferred identity labels (e.g., 'she

Scalable Algorithms for Approximate DNF Model Counting

arXiv:2601.10511v2 Announce Type: replace-cross Abstract: Model counting of Disjunctive Normal Form (DNF) formulas is a critical problem in applications such as probabilistic inference and network rel

Tutorials

SKIP: a Self-knowledge-guided Step-wise Preference Learning Framework for Concise Reasoning

arXiv:2609.17019v1 Announce Type: new Abstract: While Chain-of-Thought (CoT) reasoning has been proven to be effective, it often leads to overthinking, resulting in computational overhead, inference l

tutorialsarxiv-cs-ai

Upgraded my local setup with 2 rtx pros and it's amazing.

model-releasesr-localllama

Follow up post of https://www.reddit.com/r/LocalLLaMA/s/nGMyKswrch. Thanks everyone who replied. I didn't change the specs. Might be loosing some of the memory bandwidth but will scale in future if I

An Incomplete Loop: Deductive, Inductive, and Abductive Reasoning in Language Models

model-releasesarxiv-cs-cl

arXiv:2404.03028v4 Announce Type: replace Abstract: Modern language models (LMs) can learn to perform new tasks in different ways: in instruction following, the target task is described explicitly in

Announcing instance preference lists for Amazon SageMaker AI training jobs

model-releasesaws-ml-blog

Amazon SageMaker AI now offers instance preference lists for training and processing jobs. Specify an ordered list of up to five instance types, and SageMaker AI automatically launches on the first ty

Agents

Bayesian Intelligence from the Outside

arXiv:2609.14724v1 Announce Type: new Abstract: Inferring intelligence from observable behavior is a foundational challenge in artificial intelligence. We develop a theory of Bayesian intelligence for

agentsarxiv-cs-ai

Bench2Dex: Benchmarking Visuo-Tactile Bimanual Dexterous Manipulation Across Dexterous Hands

arXiv:2609.15726v1 Announce Type: cross Abstract: Tactile sensing provides contact information that can be difficult to infer from vision alone, but tactile hardware for dexterous hands has not conver

Biquaternionic Space with Complex-valued Attention for Temporal Knowledge Graph Completion

arXiv:2609.14279v1 Announce Type: cross Abstract: Temporal knowledge graph embedding (TKGE) models infer missing facts in knowledge graphs that evolve over time. Many existing models use a single geom

Convergent Emergence of In-Context Learning Across Modalities

arXiv:2609.14011v1 Announce Type: new Abstract: Few-shot in-context learning (ICL), the capacity of a model to infer abstract patterns from input-output examples provided in its prompt and apply them

Don't Send What You Don't Need: Question-Guided Token Pruning as a Privacy Defense for Vision-Language Models

arXiv:2609.15671v1 Announce Type: cross Abstract: Visual Question Answering (VQA) with Vision-Language Models (VLMs) is increasingly used in privacy-sensitive and bandwidth-constrained settings. Feder

local-aiarxiv-cs-ai

Drift-Constrained Optimization: Only Direction Matters in Fine-Tuning Instruct Models

arXiv:2609.13680v1 Announce Type: new Abstract: Fine-tuning instruct models often improves target performance while inducing behavioral drift from the reference model, which can degrade existing capab

local-aiarxiv-cs-ai

Tools

During an outage, every second matters. That is one of the reasons OpenAI is using @cerebras internally. @seanlie describes how fast inferen…

During an outage, every second matters. That is one of the reasons OpenAI is using @cerebras internally. @seanlie describes how fast inference is being used for incident response and critical research

toolsswyx--x

DynEoMT: Learning Object Dynamicity from Online Segmentation Queries

model-releasesarxiv-cs-cv

arXiv:2609.14466v1 Announce Type: new Abstract: Video segmentation models recognize and track objects over time, but they do not indicate whether each segmented region moves independently of the obser

Agents

Enabling Streaming User Transcription in Full-Duplex Speech-to-Speech Models

arXiv:2609.15759v1 Announce Type: new Abstract: Full-duplex speech-to-speech (S2S) models enable natural conversational AI by allowing simultaneous listening and speaking. However, these models typica

agentsarxiv-cs-cl

Tutorials

Ergodic Control and Controlled Diffusion for Robot Learning: Review and Tutorial

arXiv:2609.13295v1 Announce Type: cross Abstract: Diffusion learning leverages the statistical mechanism of diffusion processes for learning, reasoning, and inferring complex distributions from data.

tutorialsarxiv-cs-lg

Forty Shades of Blue: Quality-Diversity Alignment via Mode-Conditioned Reinforcement Learning

arXiv:2609.14896v1 Announce Type: cross Abstract: A notable byproduct of LLM alignment training is mode collapse: the progressive loss of output diversity that narrows a model's expressivity at infere

From objective discovery to prediction of global ocean eco-provinces: A pathway for trustworthy learning

arXiv:2609.13206v1 Announce Type: cross Abstract: Marine ecosystems are increasingly impacted by climate change, necessitating tools to identify and predict spatial habitat information. To build such

researcharxiv-cs-lg

Generalization Can Emerge in Tabular Foundation Models From a Single Table

arXiv:2511.09665v1 Announce Type: cross Abstract: Deep tabular modelling increasingly relies on in-context learning where, during inference, a model receives a set of (x,y) pairs as context and predic

Grouped Value Attention: Efficient KV Caching via On-Demand Key Reconstruction

model-releasesarxiv-cs-lg

arXiv:2609.13285v1 Announce Type: cross Abstract: The KV cache is a primary bottleneck for Transformer decoding: its memory footprint and cache-read traffic grow with sequence length. Grouped-query at

GRPO-QM: Target Preserving Exploration for Quantum Tomography

arXiv:2609.14711v1 Announce Type: new Abstract: Reward-based learning can alter the very posterior distribution that scientific inference aims to estimate. GRPO-QM sidesteps this by learning only an e

safetyarxiv-cs-lg

Language-Guided Representation Learning for Robust Cross-Sensor Material Recognition

model-releasesarxiv-cs-cl

arXiv:2609.14783v1 Announce Type: cross Abstract: Robots need touch to manipulate objects safely and reliably, as many properties, such as softness, texture, and contact stability, are hard to infer f

Learning Communication-Conditioned Generative Policies for Decentralized Multi-Agent Collision Avoidance

arXiv:2609.14268v1 Announce Type: new Abstract: In this work, we propose a decentralized communication-conditioned generative framework for multi-agent collision avoidance. Agents generate short-horiz

local-aiarxiv-cs-ro

Tutorials

Learning to Coach for Experiential Learning

arXiv:2609.15851v1 Announce Type: new Abstract: Language models can learn from experience, but raw solution trajectories are often too long and noisy to provide effective guidance. In this work, we pr

tutorialsarxiv-cs-cl

Lightning Weave: Improving the Accuracy-Efficiency Frontier of Reasoning Models through Capability Composition

arXiv:2609.14708v1 Announce Type: new Abstract: A core goal of efficient reasoning is to improve the accuracy-efficiency frontier. However, jointly improving reasoning accuracy and inference efficienc

Map Users and Mapmakers: The Scope of Cognitive Attribution from Acquired Representations

arXiv:2609.13879v1 Announce Type: new Abstract: An acquired representation can enlarge a system's cognitive repertoire without transferring the capacities exercised in producing that representation. T

Merging the Knowledge of LLMs for Automatic Speech Recognition

arXiv:2609.15743v1 Announce Type: new Abstract: Automatic speech recognition (ASR) systems, trained on paired speech-text data, have been improved by leveraging language models (LMs) trained on text-o

researcharxiv-cs-cl

Pedestrian Crossing Intent Classification From Event-Based Vision Using Convolutional Spiking Neural Networks With Temporal Augmentation

arXiv:2609.13328v1 Announce Type: cross Abstract: Anticipating whether a pedestrian will cross the road is safety-critical for autonomous vehicles, requiring real-time inference under challenging cond

Programs as Singularities

model-releasesarxiv-cs-lg

arXiv:2504.08075v2 Announce Type: replace-cross Abstract: We develop a correspondence between the structure of Turing machines and the structure of singularities of real analytic functions, based on c

Reason What Matters: Retrieval-Grounded Reasoning for Universal Multimodal Embeddings

arXiv:2609.15296v1 Announce Type: new Abstract: Universal multimodal embedding (UME) learns unified representations across modalities, enabling a single model to support diverse retrieval tasks. Recen

Scaling Telco Autonomy: Leveraging GNNs with Distributed GraphFlow

model-releasesgoogle-cloud-ai

The telecommunications industry is currently undergoing a paradigm shift, moving from traditional manual human-driven operations to fully Autonomous Network Operations. Modern networks have grown incr

SparseTalk - Sparsifying 3D Gaussian Language Fields for Efficient 3D Visual Question Answering

arXiv:2609.15137v1 Announce Type: new Abstract: 3D Gaussian language fields provide an explicit, spatially grounded representation for 3D visual question answering (VQA), but their dense semantic feat

researcharxiv-cs-cv

T-LoopFormer: Token-Level Elastic-Depth Looped Transformers for Latent Reasoning With Dynamic Routing

arXiv:2609.15160v1 Announce Type: new Abstract: Looped Transformers have recently demonstrated strong performance in both reasoning and language tasks by reusing a shared set of parameters across mult

The Theory of Mind Utility: A Formal Account of Mentalizing

arXiv:2606.12721v3 Announce Type: replace Abstract: Inferring another person's beliefs requires reconstructing their information access history: what they encountered, in what order, from whom, and wi

local-aiarxiv-cs-ai

To Each Language Its Tokenizer: Modular Tokenizers for Efficient Multilingual LLMs

arXiv:2609.15528v1 Announce Type: new Abstract: Multilingual Large Language Models (LLMs) traditionally rely on a single vocabulary shared by all supported languages, which can lead to uneven compress

safetyarxiv-cs-cl

Uncertainty-Aware Calibrated Clinical Text Classification with Large Language Models

arXiv:2509.19375v2 Announce Type: replace-cross Abstract: Large language models are increasingly used for clinical text classification, where overconfident misclassifications can directly affect patie

Hardware

When Faster VLA Deployment Changes Closed-Loop Behavior: Task Success-Latency Analysis of SmolVLA Across PyTorch and ONNX Variants

arXiv:2609.14146v1 Announce Type: cross Abstract: Vision-language-action (VLA) deployment can reduce inference latency while changing closed-loop task behavior. We evaluate HuggingFaceVLA/smolvla_libe

hardwarearxiv-cs-lg