Search: “models”

Position: Profiling Game Worlds by Transition Complexity

arXiv:2608.18079v1 Announce Type: new Abstract: Game world modeling (GWM) and reinforcement learning (RL) are often confounded because research papers rarely quantify how difficult the underlying tran

20 Aug 2026

Same Facts, Different Updates: Inference Setup Shapes LLM Behavior in Medical Allocation

DGX agent

arXiv:2608.18108v1 Announce Type: cross Abstract: Large language models are being incorporated into sensitive and important decision-making processes across nearly all fields. While prior work studies

safetyarxiv-cs-ai

20 Aug 2026

Task-Conditioned Least-Privilege Learning for Executable Terminal and MCP Agents

arXiv:2608.18351v1 Announce Type: cross Abstract: Tool-using large language-model agents can complete a task while exercising authority that the user did not grant or the task does not need, causing e

20 Aug 2026

VTONQA: A Multi-Dimensional Quality Assessment Dataset for Virtual Try-on

arXiv:2601.02945v2 Announce Type: replace Abstract: With the rapid development of e-commerce and digital fashion, image-based virtual try-on (VTON) has attracted increasing attention. However, existin

20 Aug 2026

Certified but Private: Scalable Zero-Knowledge Proofs for Neural Network Guarantees

arXiv:2608.17070v1 Announce Type: new Abstract: With the growing deployment of machine learning models, formal guarantees of the robustness and fairness of these models have become increasingly import

safetyarxiv-cs-lg

CKAA: Cross-subspace Knowledge Alignment and Aggregation for Robust Continual Learning

arXiv:2507.09471v2 Announce Type: replace Abstract: Continual Learning (CL) empowers AI models to continuously learn from sequential task streams. Recently, parameter-efficient fine-tuning (PEFT)-base

Research

Encoded but Not Actionable: Auditing the Decode-Generate-Steer Gap in Frozen LLMs for Geometric Constraints

arXiv:2608.17843v1 Announce Type: cross Abstract: Large language models (LLMs) have demonstrated strong performance on structured reasoning tasks, but what they encode and whether it informs model beh

researcharxiv-cs-ai

Foundation Agents Meet Agentic Deep Research: Evidence-Grounded Clinical Code Forecasting

arXiv:2608.17075v1 Announce Type: cross Abstract: Next-encounter ICD forecasting predicts which standardized diagnosis codes will be documented at a future visit from the longitudinal record available

Local Ai

Post-Train NVIDIA Cosmos 3 Edge for On-Device Robot Control

NVIDIA’s Cosmos 3 Edge is a 4‑billion‑parameter omni‑model (with a 2‑billion‑parameter Nemotron reasoner) that can run on an NVIDIA Jetson Thor, providing on‑device policy inference for robot manipula

local-ainvidia-developer

Local Ai

Predicting Male Domestic Violence Using Explainable Ensemble Learning and Exploratory Data Analysis

arXiv:2403.15594v4 Announce Type: replace-cross Abstract: Domestic violence is commonly viewed as a gendered issue that primarily affects women, which tends to leave male victims largely overlooked. T

local-aiarxiv-cs-lg

Replit Free Mode, powered by @OpenAI GPT-5.6 Luna. Let’s make intelligence accessible to everyone.

Replit has introduced a free mode powered by OpenAI’s GPT‑5.6 Luna model, announced on 19 August 2026. The service offers real‑time AI assistance for coding and collaboration at no cost, aiming to bro

model-releasesopenai--x

SE-MoLoRA: Shared-Expert LoRA Adapters for Domain-Specific Photographic Assessment

arXiv:2608.17514v1 Announce Type: new Abstract: Vision-language models can describe images fluently, but they often fail to provide actionable photographic critique because semantic content and aesthe

Local Ai

Seeing is Free, Speaking is Not: Uncovering the True Energy Bottleneck in Edge VLM Inference

arXiv:2607.09520v2 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) are the perceptual backbone of embodied AI, but their energy footprint on edge hardware remains poorly understoo

local-aiarxiv-cs-ai

StartupBench: Benchmarking General-Purpose Agents on Market-Validated End-to-End Workflows

arXiv:2608.17800v1 Announce Type: new Abstract: Recent advances in Large Language Models(LLMs) and agents have substantially improved the ability of AI systems to execute complex tasks. Yet existing b

Stop Anthropomorphisizing Intermediate Tokens: Qwen3.8 doesn't 'overthink'

Intermediate tokens, called 'thinking' or 'reasoning' actually are nothing like it. Humans do step-by-step reasoning leading to the conclusion. LLMs use intermediate traces to augment their prompt. Th

Applications

TabNSM: Neural Sparse Mixer for Tabular Regression

arXiv:2608.18026v1 Announce Type: new Abstract: Large-scale, high-dimensional tabular regression remains challenging: tree-based models are robust but lack end-to-end representation learning, while de

applicationsarxiv-cs-lg

The Emergence of Lab-Driven Alignment Signatures: A Psychometric Framework for Auditing Latent Bias and Compounding Risk in Generative AI

arXiv:2602.17127v2 Announce Type: replace Abstract: Large language models increasingly serve as reasoning layers in multi-agent systems, where one provider's models may generate, judge, and summarize

safetyarxiv-cs-cl

AA is the reason for Qwen3.8 27B shipped with xhigh

I know why Qwen3.8 27B shipped with xhigh reasoning as default, it's to do its best in benchmarks. Models from top labs often get benchmarked at multiple reasoning levels, but that same treatment does

ChainSpace: A Chained-Reasoning Paradigm for Spatial Intelligence

arXiv:2608.15788v1 Announce Type: new Abstract: Spatial intelligence requires foundation models to maintain coherent spatial state across interactions with the physical world. However, existing data-c

Research

Do Uncertainty Signals Help? A Systematic Study of Uncertainty-Aware Decoding with Rollback Mechanisms

arXiv:2608.14653v1 Announce Type: cross Abstract: Prediction uncertainty is a widely adopted metric for quantifying model confidence, with downstream applications spanning model explanation, data sele

researcharxiv-cs-ai

Does a Tool Result Carry More Authority Than Plain Text? Three Prospective Studies of False-Claim Adoption in a Synthetic Assignment Task with Claude Opus 5

arXiv:2608.14992v1 Announce Type: new Abstract: Language-model systems increasingly read from stores they also write to, so a claim that was merely written earlier can return looking retrieved. We tes

Does the LM Head Create a Harmful Gradient Bottleneck? A Causal Test

model-releasesarxiv-cs-cl

arXiv:2608.16671v1 Announce Type: new Abstract: The language-model head maps a hidden state of width D to a vocabulary of size V, so its transpose can return at most D independent directions to the Tr

Don't ignore llama.cpp RPC with old hardware. Results of a 5070 Ti and 1080 Ti over gigabit ethernet: it's actually functional.

Results up front: I had to prioritize prefill or token generation - there was no happy medium. Using UD-Q4_K_XL, q8 kv cache, and 96k max context: focus on generation (MTP = 2): 350 pp and 36 tg @ 12k

Enhancing the Non-Functional Quality Compliance of LLM-Generated Code through Quality-Aware Preference Learning

arXiv:2503.09020v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have been widely adopted in commercial code completion engines, significantly enhancing coding efficiency and pro

FirstDiff: One-Step Diffusion-Based Anomaly Detection for Multivariate Time Series via Initial Noise Prediction

arXiv:2608.15727v1 Announce Type: cross Abstract: Diffusion models have recently shown strong potential for multivariate time-series anomaly detection by learning the distribution of normal data throu

Research

Forward Pass Domain Adaptation (Without Cross-Layer Backpropagation)

arXiv:2608.14563v1 Announce Type: cross Abstract: Forward-Pass-Only MLP training (FPO) adapts large language models without a backward pass through the model body, achieving 2.7--3.2x the throughput o

researcharxiv-cs-ai

Gathered, Not Admitted: How Attention Brings a Latent Variable into Verbalizable Form

arXiv:2608.15022v1 Announce Type: new Abstract: Language models hold latent quantities in a form they can report on, and more of a quantity is present in that form when the task requires reusing it fl

Tutorials

Human Pose Estimation in Trampoline Gymnastics: How to Improve Performance on Extreme Poses

arXiv:2604.01322v2 Announce Type: replace Abstract: Trampoline gymnastics involves extreme human poses and uncommon viewpoints, on which state-of-the art pose estimation models tend to under-perform.

tutorialsarxiv-cs-cv

HyMem: Hierarchical Context Management for Long-Horizon Agents via Information Isolation

arXiv:2608.15703v1 Announce Type: new Abstract: Large language model (LLM) agents often perform poorly on complex, long-horizon tasks because their context becomes increasingly cluttered over time. As

Improving Influence-based Instruction Tuning Data Selection for Balanced Learning of Diverse Capabilities

arXiv:2501.12147v2 Announce Type: replace-cross Abstract: Selecting appropriate training data is crucial for instruction fine-tuning of large language models (LLMs), which aims to (1) elicit strong ca

Ling-3.0 (BailingMoE3) lands in llama.cpp mainline - Quick benchmarks on Intel Arc B580

Finally llama.cpp now officially supports Ling-3.0! (Starting from build b10472+) If you want to run them locally, bartowski has already released the GGUF imatrix quantizations for both models: - Ling

Listen, Reason, and Segment: Aligning LALMs with Editorial Judgment for Media Chapterization

arXiv:2608.16539v1 Announce Type: cross Abstract: Large Audio Language Models (LALMs) have made rapid progress on standardized benchmarks, yet their deployment in practical media workflows, curation,

LLMs for Zero-Shot Threat Detection via Structured Risk Indicators

model-releasesarxiv-cs-lg

arXiv:2608.16508v1 Announce Type: cross Abstract: We propose a two-stage large language model (LLM) framework for zero-shot detection of insider threats and advanced persistent threats (APTs) from het

Local Qwen 3.8 27B vs GPT‑5.6 Terra vs Grok 4.6

I gave three AI models the same brief: build a premium Three.js fragrance launch site from the same Git baseline, independently and with no collaboration. Three very different results. Here’s the full

model-releasesr-ollama

MetaReason: Precise Interleaved Multimodal Reasoning via Editing Meta Information for Solving Geometry Problems

arXiv:2608.15006v1 Announce Type: cross Abstract: Although visual reasoning is crucial for solving complex geometry tasks, existing vision-language models rely heavily on text-only reasoning. Some rec

MLLM-Guided Semantic Correction for Text-to-Video Generation

arXiv:2608.16513v1 Announce Type: cross Abstract: Recent advances in diffusion models and Transformer architectures have led to significant progress in text-to-video generation. However, these models

safetyarxiv-cs-ai

Not All Attention Is Equal: A Quantitative Survey of the EEI Trade-off

arXiv:2608.15459v1 Announce Type: cross Abstract: Attention mechanisms have driven machine learning for a decade, from neural machine translation to language models that do general-purpose reasoning.

PL-Guard: Probabilistic Logic Reasoning for LLM Guardrails

arXiv:2608.15673v1 Announce Type: cross Abstract: Large language model guardrails can be viewed as policy-consistency problems: a system must determine which policy-relevant facts hold in a prompt-res

RecurrentGPT: Expressive Depth through Recurrent Modulation in Transformers

model-releasesarxiv-cs-cl

arXiv:2608.15062v1 Announce Type: new Abstract: Scaling transformer language models creates an inherent tension between expressivity and memory efficiency. While unique weights across layers preserve

SchurQuant: Groupwise Discrete Optimization for Layer-Wise LLM Quantization

model-releasesarxiv-cs-lg

arXiv:2608.15567v1 Announce Type: new Abstract: Weight-only post-training quantization (PTQ) enables the deployment of large language models under tight memory budgets, but accuracy often collapses at

Shorter, but Still Trustworthy? An Empirical Study of Chain-of-Thought Compression

model-releasesarxiv-cs-cl

arXiv:2604.04120v2 Announce Type: replace Abstract: Long chain-of-thought (Long-CoT) reasoning models have motivated a growing body of work on compressing reasoning traces to reduce inference cost, ye

SkillCommit: Evolving Agent Skills through Behaviorally Validated Scope Expansion

arXiv:2608.15165v1 Announce Type: new Abstract: Large language model (LLM) agents can continually improve without parameter updates by converting historical experience into reusable procedural knowled

Synthetic Image Detection with CLIP: Understanding and Assessing Predictive Cues

arXiv:2602.12381v2 Announce Type: replace Abstract: Recent generative models produce near-photorealistic images, challenging the trustworthiness of photographs. Synthetic image detection (SID) methods

TwinGridShield: Consequence-Aware Runtime Authorization for LLM Grid-Agent Actions

arXiv:2608.15391v1 Announce Type: new Abstract: Large language model (LLM)-assisted energy-management tools can translate natural-language context into structured grid commands, but syntactic validity

safetyarxiv-cs-ai

When Agentic Executions Fail: Detecting and Localizing Runtime Faults from Telemetry

arXiv:2608.14680v1 Announce Type: new Abstract: Reliability in LLM-based agentic systems is a property of the whole execution (its tool calls, model calls, guardrails, and inter-agent messages), not o

Agentic Transaction: Towards ACID-Compliant Agent Systems

arXiv:2608.13900v1 Announce Type: cross Abstract: Large language model (LLM) agents are evolving from conversational assistants into autonomous systems that execute long-horizon tasks through reasonin

17 Aug 2026

DeaMoE: Efficient MoE Structure for Fast Small-Batch Decoding

arXiv:2608.14385v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) models have been widely adopted in real-time interactive applications such as coding assistants, real-time audio-video intera

17 Aug 2026

Generating Benchmark Health Data Using a Tabular Diffusion Transformer

arXiv:2608.14496v1 Announce Type: cross Abstract: Cross-Tabular Data Generation (CTDG) seeks to learn a generative model from multiple heterogeneous tables and produce new synthetic tabular datasets.