Search: “models”

arXiv:2605.07234v1 Announce Type: cross Abstract: Large language models (LLMs) support long-context inference but suffer from substantial memory and runtime overhead due to Key-Value (KV) Cache growth

local-aiarxiv-cs-ai

Rethinking Dense Optical Flow without Test-Time Scaling

DGX agent

arXiv:2605.08000v1 Announce Type: new Abstract: Recent progress in dense optical flow has been driven by increasingly complex architectures and multi-step refinement for test-time scaling. While these

model-releasesarxiv-cs-cv

11 May 2026

Revisiting Transformer Layer Parameterization Through Causal Energy Minimization

arXiv:2605.07588v1 Announce Type: cross Abstract: Transformer blocks typically combine multi-head attention (MHA) for token mixing with gated MLPs for token-wise feature transformation, yet many choic

Rollback-Free Stable Brick Structures Generation

arXiv:2605.06947v1 Announce Type: new Abstract: While autoregressive models have advanced 3D generation, creating physically stable brick structures remains a challenge due to the strict requirements

safetyarxiv-cs-lg

Rubric-Grounded RL: Structured Judge Rewards for Generalizable Reasoning

arXiv:2605.08061v1 Announce Type: new Abstract: We argue that decomposing reward into weighted, verifiable criteria and using an LLM judge to score them provides a partial-credit optimization signal:

SCENE: Recognizing Social Norms and Sanctioning in Group Chats

model-releasesarxiv-cs-cl

arXiv:2605.07823v1 Announce Type: new Abstract: Online group chats are social spaces with implicit behavior patterns that, when broken, are often met with social sanctioning from the group. The abilit

SmellBench: Evaluating LLM Agents on Architectural Code Smell Repair

model-releasesarxiv-cs-cl

arXiv:2605.07001v1 Announce Type: cross Abstract: Architectural code smells erode software maintainability and are costly to repair manually, yet unlike localized bugs, they require cross-module reaso

Target-Aware Data Augmentation for SAT Prediction

arXiv:2605.06931v1 Announce Type: new Abstract: Learning-based approaches to NP-hard problems have shown increasing promise, but their progress is fundamentally constrained by the high cost of generat

TEA-Bench: A Systematic Benchmarking of Tool-enhanced Emotional Support Dialogue Agent

arXiv:2601.18700v2 Announce Type: replace Abstract: Emotional Support Conversation requires not only affective expression but also grounded instrumental support to provide trustworthy guidance. Howeve

Teacher-Feature Drifting: One-Step Diffusion Distillation with Pretrained Diffusion Representations

arXiv:2605.07327v1 Announce Type: new Abstract: Sampling from pretrained diffusion and flow-matching models typically requires many forward passes to generate diverse and high-fidelity images. Existin

Traffic Scenario Orchestration from Language via Constraint Satisfaction

model-releasesarxiv-cs-ro

arXiv:2605.06966v1 Announce Type: new Abstract: Autonomous vehicles (AVs) require extensive testing in simulation, but test case generation for driving scenarios is laborious. The desired scenarios ar

Trajectory as the Teacher: Few-Step Discrete Flow Matching via Energy-Navigated Distillation

arXiv:2605.07924v1 Announce Type: cross Abstract: Discrete flow matching generates text by iteratively transforming noise tokens into coherent language, but may require hundreds of forward passes. Dis

Transformer-Based Wildlife Species Classification from Daily Movement Trajectories

arXiv:2605.06726v1 Announce Type: new Abstract: Inferring the identity of wildlife species from daily movement data alone is a challenging task. We train sequence models on large-scale, 7-species GPS

researcharxiv-cs-lg

UNCOM: Zero-shot Context-Aware Command Understanding for Tabletop Scenarios

arXiv:2410.06355v3 Announce Type: replace-cross Abstract: This paper presents UNCOM, a novel hybrid framework for interpreting natural human commands in tabletop scenarios. The system integrates multi

Ship code within minutes with the Gemini CLI DevOps Extension

model-releasesgoogle-cloud-ai

With AI coding tools like Antigravity and Claude Code, I can build a working web app in record time. But deploying it? That's where I'd historically lose the rest of the afternoon to Dockerfiles, IAM

8 May 2026

Agents

'Tis the year of open source LLMs in agents!

'Tis the year of open source LLMs in agents! .@BraceSproul changed our org's internal model in Fleet from Sonnet 4.6 to Kimi K2.6 and I didn't even notice. Open models are already good enough for most

agentsharrison-chase--x

8 May 2026

Hardware

A Physics-Aware Framework for Short-Term GPU Power Forecasting of AI Data Centers

arXiv:2605.04074v1 Announce Type: new Abstract: AI data centers experience rapid fluctuations in power demand due to the heterogeneity of computational tasks that they have to support. For example, th

hardwarearxiv-cs-lg

Advancing Aesthetic Image Generation via Composition Transfer

arXiv:2605.04609v1 Announce Type: new Abstract: Composition is a cornerstone of visual aesthetics, influencing the appeal of an image. While its principles operate independently of specific content, i

Aes3D: Aesthetic Assessment in 3D Gaussian Splatting

model-releasesarxiv-cs-cv

arXiv:2605.05155v1 Announce Type: new Abstract: As 3D Gaussian Splatting (3DGS) gains attention in immersive media and digital content creation, assessing the aesthetics of 3D scenes becomes important

Back to Blackwell: Closing the Loop on Intransitivity in Multi-Objective Preference Fine-Tuning

arXiv:2602.19041v2 Announce Type: replace Abstract: A recurring challenge in preference fine-tuning (PFT) is handling extit{intransitive} (i.e., cyclic) preferences. Intransitive preferences often ste

Behind the Scenes Hardening Firefox with Claude Mythos Preview

model-releasessimon-willison

Behind the Scenes Hardening Firefox with Claude Mythos Preview Fascinating, in-depth details on how Mozilla used their access to the Claude Mythos preview to locate and then fix hundreds of vulnerabil

Closed-Loop Vision-Language Planning for Multi-Agent Coordination

arXiv:2502.10148v3 Announce Type: replace Abstract: Cooperative multi-agent reinforcement learning (MARL) struggles with sample efficiency, interpretability, and generalization. While Large Language M

Local Ai

comfyui-lora-FindingLora - a Lora Loader with fuzzy search, one click chaining, bookmarks and triggers.

local-air-stablediffusion

ComfyUI-Lora-FindingLora is a specialized loader extension for the ComfyUI image generation framework that streamlines LoRA (Low-Rank Adaptation) model management through fuzzy search functionality, e

Direct Product Flow Matching: Decoupling Radial and Angular Dynamics for Few-Shot Adaptation

arXiv:2605.05054v1 Announce Type: new Abstract: Recent flow matching (FM) methods improve the few-shot adaptation of vision-language models, by modeling cross-modal alignment as a continuous multi-ste

safetyarxiv-cs-cv

Evaluating Semantic Fragility in Text-to-Audio Generation Systems Under Controlled Prompt Perturbations

arXiv:2603.13824v2 Announce Type: replace-cross Abstract: Recent advances in text-to-audio generation enable models to translate natural-language descriptions into diverse musical output. However, the

safetyarxiv-cs-ai

FAAST: Forward-Only Associative Learning via Closed-Form Fast Weights for Test-Time Supervised Adaptation

arXiv:2605.04651v1 Announce Type: cross Abstract: Adapting pretrained models typically involves a trade-off between the high training costs of backpropagation and the heavy inference overhead of memor

researcharxiv-cs-cl

From Priors to Perception: Grounding Video-LLMs in Physical Reality

arXiv:2605.04515v1 Announce Type: new Abstract: While Video Large Language Models (Video-LLMs) excel in general understanding, they exhibit systematic deficits in fine-grained physical reasoning. Exis

Heterogeneous Ordinal Structure Learning with Bayesian Nonparametric Complexity Discovery

arXiv:2605.04191v1 Announce Type: cross Abstract: Public attitudes toward artificial intelligence are heterogeneous, ordinally measured, and poorly captured by any single dependency graph. Existing or

Joint Treatment Effect Estimation from Incomplete Healthcare Data: Temporal Causal Normalizing Flows with LLM-driven Evolutionary MNAR Imputation

arXiv:2605.05125v1 Announce Type: new Abstract: Target trial emulation (TTE) enables causal questions to be studied with observational data when randomized controlled trials (RCTs) are infeasible. Yet

Jordan-RoPE: Non-Semisimple Relative Positional Encoding via Complex Jordan Blocks

model-releasesarxiv-cs-cl

arXiv:2605.04217v1 Announce Type: cross Abstract: Relative positional encodings determine which functions of query-key lag can enter the primitive attention logit. RoPE supplies a rotary phase, while

LUCAS-MEGA: A Large-Scale Multimodal Dataset for Representation Learning in Soil-Environment Systems

arXiv:2605.04323v1 Announce Type: new Abstract: Understanding soil is fundamental to agriculture, carbon cycling, and environmental sustainability, yet progress is limited by fragmented and heterogene

Mitigating Label Shift in Tabular In-Context Learning via Test-Time Posterior Adjustment

arXiv:2605.04363v1 Announce Type: new Abstract: TabPFN has recently gained attention as a foundation model for tabular datasets, achieving strong performance by leveraging in-context learning on synth

researcharxiv-cs-lg

Physics-Grounded Multi-Agent Architecture for Traceable, Risk-Aware Human-AI Decision Support in Manufacturing

arXiv:2605.04003v1 Announce Type: cross Abstract: High-precision CNC machining of free-form aerospace components requires bounded compensations informed by inspection, simulation, and process knowledg

Applications

Rethinking Convolutional Networks for Attribute-Aware Sequential Recommendation

arXiv:2605.04723v1 Announce Type: cross Abstract: Attribute-aware sequential recommendation entails predicting the next item a user will interact with based on a chronologically ordered history of pas

applicationsarxiv-cs-lg

SAMIC: A Lightweight Semantic-Aware Mamba for Efficient Perceptual Image Compression

arXiv:2605.04560v1 Announce Type: new Abstract: Perceptual image compression focuses on preserving high visual quality under low-bitrate constraints. Most existing approaches to perceptual compression

Sharp Capacity Thresholds in Linear Associative Memory: From Winner-Take-All to Listwise Retrieval

arXiv:2605.05189v1 Announce Type: cross Abstract: How many key-value associations can a dimes d linear memory store? We show that the answer depends not only on the d^2 degrees of freedom in the memor

Local Ai

Stabilizing LLM Supervised Fine-Tuning via Explicit Distributional Control

arXiv:2605.04468v1 Announce Type: cross Abstract: Post-training large language models (LLMs) often suffers from catastrophic forgetting, where improvements on a target objective degrade previously acq

local-aiarxiv-cs-cl

Stage Light is Sequence^2: Multi-Light Control via Imitation Learning

arXiv:2605.03660v1 Announce Type: cross Abstract: Music-inspired Automatic Stage Lighting Control (ASLC) has gained increasing attention in recent years due to the substantial time and financial costs

The Predictive-Causal Gap: An Impossibility Theorem and Large-Scale Neural Evidence

arXiv:2605.05029v1 Announce Type: new Abstract: We report a systematic failure mode in predictive representation learning. Across 2695 neural network configurations trained to predict linear-Gaussian

UI2Code^N: UI-to-Code Generation as Interactive Visual Optimization

arXiv:2511.08195v3 Announce Type: replace Abstract: UI-to-code aims to translate UI screenshots into executable front-end code. Despite progress with vision-language models (VLMs), most existing metho

safetyarxiv-cs-cv

VCBench: Benchmarking LLMs in Venture Capital

arXiv:2509.14448v2 Announce Type: replace Abstract: Benchmarks such as SWE-bench and ARC-AGI demonstrate how shared datasets accelerate progress toward artificial general intelligence (AGI). We introd

What Happens Inside Agent Memory? Circuit Analysis from Emergence to Diagnosis

arXiv:2605.03354v1 Announce Type: new Abstract: Agent memory failures are silent: an LLM-based agent can produce a fluent response even when it fails to extract, retain, or retrieve the information ne

Agents

What You Think is What You See: Driving Exploration in VLM Agents via Visual-Linguistic Curiosity

arXiv:2605.03782v1 Announce Type: new Abstract: To navigate partially observable visual environments, recent VLM agents increasingly internalize world modeling capabilities into their policies via exp

agentsarxiv-cs-ai

A Framework for Exploring and Disentangling Intersectional Bias: A Case Study in Fetal Ultrasound

model-releasesarxiv-cs-cv

arXiv:2605.02942v1 Announce Type: cross Abstract: Bias in medical AI is often framed as a problem of representation. However, in image-based tasks such as fetal ultrasound, performance disparities can

ABD: Default Exception Abduction in Finite First Order Worlds

arXiv:2602.18843v3 Announce Type: replace Abstract: We introduce ABD, a benchmark for default-exception abduction over finite first-order worlds. Given a background theory with an abnormality predicat

AcademiClaw: When Students Set Challenges for AI Agents

arXiv:2605.02661v1 Announce Type: new Abstract: Benchmarks within the OpenClaw ecosystem have thus far evaluated exclusively assistant-level tasks, leaving the academic-level capabilities of OpenClaw

AI Agents for Inventory Control: Human-LLM-OR Complementarity

arXiv:2602.12631v2 Announce Type: replace-cross Abstract: Inventory control is a fundamental operations problem in which ordering decisions are traditionally guided by theoretically grounded operation

Analysis and Explainability of LLMs Via Evolutionary Methods

arXiv:2605.02930v1 Announce Type: cross Abstract: Evolutionary methods have long been useful for analysis and explanation in genetics, biology, ecology, and related fields. In this work, we extend the

researcharxiv-cs-lg