Search: “inference”

Stable Miscalibration in Large Language Models: A Practical View of High-Confidence Errors

arXiv:2608.13591v1 Announce Type: new Abstract: High-confidence errors in large language models are often treated as evidence of fragile internal inference. We study a different possibility: stable mi

17 Aug 2026

Hardware

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The conditional superiority of fast silicon sampling

DGX agent

arXiv:2608.14079v1 Announce Type: new Abstract: Silicon sampling can produce surprisingly good population estimates at times. Does doing it fast attenuate such fidelity? In this study, we extend and a

hardwarearxiv-cs-cl

17 Aug 2026

Your Probabilistic JEPA Is Secretly a Hidden Markov Model: A State-Space Interpretation of Joint-Embedding Predictive Learning

arXiv:2608.13621v1 Announce Type: new Abstract: A hidden Markov model (HMM) combines three roles: inference of a hidden-state belief from observations, propagation through a Markov transition, and emi

17 Aug 2026

Hardware

Fantastic initiative by @nvidia. “Circular financing” is thrown around as a pseudo intellectual gotcha, while everyone in the AI infrastruct…

Fantastic initiative by @nvidia. “Circular financing” is thrown around as a pseudo intellectual gotcha, while everyone in the AI infrastructure business is witnessing demand curves that are so rapidly

hardwaretogether-ai--x

Ollama works locally, but my coding-agent integration does not

I’m running Ollama on an M4 Pro Mac with 48 GB unified memory and testing local coding models for repository work. Direct Ollama inference is fine. Qwen3.8 27B-MLX runs well enough for me, and the loc

model-releasesr-ollama

Qwen3.8-27b on RTX 3090 - 82 tps single request, up to 672 tps peak

Hi, After a long night of optimizations, I believe I have made the fastest inference engine for Qwen3.6-28B on a 3090. Quick metrics: - 250w power capped - Up to 195k context (ships with 150k for safe

local-air-localllama

Show-off Saturday: Intel Arc B140 build.

model-releasesr-localllama

My local inference build, with: ASUS WS C422 PRO/SE 10-core Xeon W-2255 64GB ECC RAM 64GB VRAM Pimped case with TurboLEDz indicating the frequencies of the 10 xeon cores. Running llama.cpp with SYCL b

[Megathread] Qwen 3.8 27B Release Day

model-releasesr-localllama

Megathread to help with the influx of duplicate / similar posts around the release of the Qwen 3.8 27B release. Quants Fine-Tunes & Abliterations Chat Templates Inference Server Support & Configuratio

15 Aug 2026

A Bayes-Markov Neuromorphic Model of Cortical Orientation Selectivity: A Computational Re-implementation and Quantitative Simulation Study

model-releasesarxiv-cs-lg

arXiv:2608.12388v1 Announce Type: cross Abstract: The emergence of orientation selectivity in the primary visual cortex (V1) remains a central question in computational neuroscience. Shirazi's Bayes-M

A Compositional Theory of Curvature in Probabilistic Circuits

arXiv:2608.12869v1 Announce Type: cross Abstract: Probabilistic Circuits (PCs) are generative models that support exact inference and, unlike deep neural networks, admit an exact and tractable measure

safetyarxiv-cs-ai

A Hierarchical Energy-Based Model for Multimodal Cognition

arXiv:2608.12398v1 Announce Type: cross Abstract: We propose IM-LEPP (Integrated Multimodal Latent Energy-based Predictive Processing), a hierarchical, energy-based model of multimodal cognition that

AirForesight: Current-to-Future Spatial Map Imagination with Cross-Space Planning Consistency for UAV-VLN

arXiv:2608.12835v1 Announce Type: new Abstract: Unmanned Aerial Vehicle Vision-Language Navigation (UAV-VLN) requires agents to follow language instructions, infer spatial structure from sparse multi-

researcharxiv-cs-ro

DAPD: Dual-Anchored Policy Distillation

arXiv:2608.01735v2 Announce Type: replace Abstract: On-policy (self) distillation (OPSD) is increasingly adopted for language-model post-training. It strengthens the teacher with privileged informatio

safetyarxiv-cs-ai

DiCoR: Decoupled Referent Disambiguation and Contour Recalibration for Efficient Referring Remote Sensing Image Segmentation

arXiv:2608.12980v1 Announce Type: new Abstract: Referring remote sensing image segmentation (RRSIS) aims to delineate targets specified by natural language expressions in remote sensing imagery. Exist

local-aiarxiv-cs-cv

Foundation models for movement data: Are they ready for prime-time?

arXiv:2608.13316v1 Announce Type: cross Abstract: Foundation models (FMs) trained on large-scale accelerometer data have been proposed as general-purpose feature extractors for health monitoring, but

researcharxiv-cs-lg

Agents

Learning Latency-Aware Orchestration for Multi-Agent Systems

arXiv:2601.10560v2 Announce Type: replace-cross Abstract: Multi-agent systems (MAS) coordinate multiple LLM-powered agents through structured workflows, gaining reasoning power but incurring high infe

agentsarxiv-cs-ai

RAGSieve: Self-Referenced Local Contrast for Knowledge-Poison Detection in Retrieval-Augmented Generation

arXiv:2608.13010v1 Announce Type: new Abstract: Retrieval-augmented generation treats an external corpus as inference evidence, allowing injected documents to promote attacker-chosen claims. Existing

researcharxiv-cs-cl

Self-Localizing MIMO Beam Mapping for Intelligent Open RAN with Continuously Evolving Channel Memory

arXiv:2511.17007v2 Announce Type: replace-cross Abstract: Open and intelligent radio access networks (RANs) envisioned for 6G require accurate and reusable wireless channel knowledge for intelligent i

local-aiarxiv-cs-lg

Trie Automata for Constrained Decoding over Large Finite Sets

arXiv:2608.12574v1 Announce Type: new Abstract: Large language models increasingly need to generate structured outputs that conform to predefined schemas, with one common constraint being selection fr

b10413

model-releasesllama-cpp-releases

common : auto-detect spec type from draft GGUF metadata (#26814) common : auto-detect spec type from draft GGUF metadata When -md loads a local draft model without --spec-type, the sidecar inference i

GeoFlow: Efficient Driving Video Generation via Geometry-Aligned Priors

arXiv:2608.12203v1 Announce Type: new Abstract: Generative models like Diffusion Models and Flow Matching have demonstrated remarkable capabilities in synthesizing high-fidelity driving videos, but ar

researcharxiv-cs-cv

Lifecycle-Optimal Tokenization: Vocabulary Size as a Deployment-Regime-Dependent Infrastructure Parameter

model-releasesarxiv-cs-cl

arXiv:2608.11361v1 Announce Type: cross Abstract: Tokenizer vocabulary size is a foundational design choice in large language model (LLM) infrastructure, yet it is typically fixed at training time bas

Multi-Agent Embodied Autonomous Driving: From V2X Information Exchange to Shared World Models

arXiv:2606.13840v2 Announce Type: replace-cross Abstract: Autonomous driving is shifting from isolated vehicle intelligence toward multi-agent embodied systems that share perception, infer intent, and

safetyarxiv-cs-cv

Previewing Ultrafast mode: GPT-5.6 Sol at up to 14x the speed. Launching first in the OpenAI API to a select group of customers with expande…

On Aug 13 2026, OpenAI announced a preview of its “Ultrafast” mode for the GPT‑5.6 model, called Sol, which claims inference speeds up to 14× faster than current releases. The feature is initially rol

model-releasesopenai--x

Quantization-Aware Neuromorphic Architecture for Skin Lesion Classification on Resource-Constrained Devices

arXiv:2507.15958v5 Announce Type: replace-cross Abstract: On-device skin lesion analysis is constrained by the compute and energy cost of conventional CNN inference and by the need for lightweight cal

local-aiarxiv-cs-ai

Robust and Efficient Noisy-Label Time-Series Classification via Dynamic Time Warping Based Granular Ball Computing

arXiv:2608.11704v1 Announce Type: cross Abstract: Dynamic Time Warping (DTW)-based Nearest-Neighbor (NN) classifiers are effective for time-series classification but are vulnerable to mislabeled train

Semantic Lenia: Emergence of Homeostatic Solitons within the Semantic Space of Large Language Models

arXiv:2608.11657v1 Announce Type: cross Abstract: We introduce Semantic Lenia, an artificial life framework that transforms Large Language Model (LLM) inference from a static optimization problem into

When Self-Consistency Backfires: Majority Vote Hurts the Majority of Hard Science Problems for Small LLMs

arXiv:2608.11403v1 Announce Type: new Abstract: Self-consistency (SC) via majority vote is a widely used way to spend inference-time compute: sample N chains of thought, return the plurality answer. O

Applications

A Cost-Efficient Routing Pipeline for Multilingual Short-Text Classification Using Small Language Models

arXiv:2608.10939v1 Announce Type: cross Abstract: Multilingual short-text classification supports operational systems such as content moderation, customer support routing, and intent recognition, yet

applicationsarxiv-cs-ai

A matched-integrator evaluation of Hamiltonian neural networks on pendulum and Kepler dynamics

model-releasesarxiv-cs-lg

arXiv:2608.10235v1 Announce Type: new Abstract: Hamiltonian Neural Networks (HNNs) parameterize conservative dynamics through a learned scalar Hamiltonian, providing an architectural prior that is abs

Conversational Orchestration for Organic 6G

arXiv:2608.10714v1 Announce Type: cross Abstract: The Organic 6G vision of a network of networks spanning an edge-cloud continuum complemented by non-terrestrial resources requires, to realize its pro

local-aiarxiv-cs-ai

Applications

FACT: Failure-Aware Causal Training for World-Action Models

arXiv:2608.10232v1 Announce Type: cross Abstract: Recent world-action models (WAMs) show that co-training policies with future prediction can provide physical priors for action generation. Building on

applicationsarxiv-cs-ai

Flex-pi: A Multi-Stream World-Action Model with Compute Flexibility

model-releasesarxiv-cs-cv

arXiv:2608.10860v1 Announce Type: cross Abstract: World-action models (WAMs) predict the future to act better, but nearly all of them predict only RGB latents, trained purely for pixel reconstruction,

Tutorials

Hypothesis Frontier: Verifier Guided LLM and Symbolic Search for First-Order Induction

arXiv:2608.10843v1 Announce Type: new Abstract: First-order concept synthesis asks a system to infer one formula that classifies labeled objects consistently across several finite relational structure

tutorialsarxiv-cs-ai

LiquidAI/LFM2.5-VL-3B · Hugging Face

LFM2.5-VL-3B is a multimodal variant of LFM2.5, a family of hybrid models designed for on-device deployment. It builds on LFM2-VL-3B with further mid- and post-training. LFM2.5-VL-3B can process both

local-air-localllama

MERA: Model Evolution and Routing with Skill Adaptation for Agentic Systems at Scale

arXiv:2608.10333v1 Announce Type: new Abstract: LLM agents execute heterogeneous sequences of model calls within a single task: some invocations require careful reasoning, while others are structured

safetyarxiv-cs-lg

Predicting Space Groups of Double Perovskites by LLM with Dynamic Few-Shot Learning

arXiv:2608.10483v1 Announce Type: new Abstract: Double perovskites (DPs) offer broad compositional tunability, but predicting the space groups (SGs) of stable structures remains difficult because avai

safetyarxiv-cs-ai

Quantum Coordination Advantages in AI State-Tracking Tasks: Semantic Compilation and Latent Memory

arXiv:2608.11066v1 Announce Type: cross Abstract: We prove inference-time quantum coordination advantages for specified AI state-tracking tasks. A solver compresses semantic history into a future-acce

local-aiarxiv-cs-ai

Situation Graph Prediction for User Perspective Modeling

arXiv:2602.13319v2 Announce Type: replace Abstract: Perspective-aware AI requires modeling evolving internal states---goals, emotions, contexts---not merely preferences. Progress is limited by a data

Surfacing the Unsaid: CUE-Bench for Affective Stance in Chinese Discourse

arXiv:2608.10810v1 Announce Type: cross Abstract: Emotion understanding in discourse requires reasoning beyond surface sentiment because speakers often convey affect through indirect, implicit, polite

TACTICL: Task-Aware Compression of Tabular ICL Models

arXiv:2608.10837v1 Announce Type: cross Abstract: The strong performance of foundation models for tabular tasks comes at substantial inference costs. Distilling models into task-specific architectures

Tutorials

ThinkRetrieve: Retrieval-Augmented Reasoning Traces for Test-Time Scaling

arXiv:2608.10928v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) improve performance by allocating additional inference-time compute to generate extended chain-of-thought reasoning. Howev

tutorialsarxiv-cs-ai

VIDS-Seg: Towards Reliable Uncertainty Quantification in Pediatric Cardiac Ultrasound Segmentation

arXiv:2608.10903v1 Announce Type: new Abstract: Reliable clinical deployment of machine learning requires models that know when they are likely to fail, particularly for subgroups underrepresented in

safetyarxiv-cs-cv

We are in an insane run of open-weight drops. Every modality, open source is winning. This is what an open source AI summer ☀️ looks like: …

model-releasesclem-delangue--x

We are in an insane run of open-weight drops. Every modality, open source is winning. This is what an open source AI summer ☀️ looks like: 🧠 LLMs & Reasoning → DeepSeek-V4-Flash-0731 (my king 👑): 304B

Are Latent Reasoning Models Easily Interpretable?

arXiv:2604.04902v2 Announce Type: replace Abstract: Latent reasoning models (LRMs) have attracted significant research interest due to their low inference cost (relative to explicit reasoning models)

researcharxiv-cs-lg

Avalon-ToM-Bench: Evaluating Fine-Grained Theory of Mind via Asymmetric Game Mechanics

arXiv:2608.09638v1 Announce Type: new Abstract: Theory of Mind (ToM) is essential for agent interactions, yet existing evaluations either rely on static scenarios that oversimplify mental-state reason

Agents

Business Arena: Benchmarking LLM Agents in a Realistic Marketplace

arXiv:2608.08621v1 Announce Type: new Abstract: Running a business is a challenging form of intelligent work. Operators must infer opportunities from partial signals, commit capital under uncertainty,

agentsarxiv-cs-ai

Contamination Means Overestimation? A Fine-Grained Empirical Study in Code Intelligence

arXiv:2506.02791v4 Announce Type: replace-cross Abstract: In recent years, code intelligence has gained increasing importance in the field of automated software engineering. Meanwhile, the widespread