Search: “evaluation”

The Optimizer Is the Agent: Reasoning-Driven Search across Prompts, Programs, and ML Workflows

arXiv:2608.06714v1 Announce Type: new Abstract: Recent systems for optimizing prompts, programs, and ML workflows typically rely on explicit outer-loop controllers such as evolutionary search, bandits

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Agents

The Perils of Agency: How Developers Perceive, Prioritize, and Address Risks in Agentic AI Products

DGX agent

arXiv:2606.15485v2 Announce Type: replace-cross Abstract: Agentic AI systems act autonomously, use tools, adapt to context, and operate in complex real-world environments. However, these same characte

agentsarxiv-cs-ai

10 Aug 2026

The Sparsity Whisperer

model-releasesarxiv-cs-lg

arXiv:2608.06630v1 Announce Type: new Abstract: Pruning reduces the inference cost of large language models, but existing criteria primarily preserve large activations or reconstruct layer outputs. We

Toward a Causal Data Management Ecosystem for Decision Making and Agentic AI

arXiv:2608.07214v1 Announce Type: cross Abstract: Modern AI is no longer a single model but an ecosystem: classical ML predictors, deep and multimodal models, large language models, and agents, each t

UAV3DCrop: Benchmarking 3D Reconstruction in Repeated Multi-Angle UAV Crop Surveys

model-releasesarxiv-cs-cv

arXiv:2608.06404v1 Announce Type: new Abstract: Accurate 3D crop monitoring underpins data-driven precision agriculture by enabling field-scale analysis of plant structure, growth dynamics, and manage

UniCycleFlow: Bidirectional Unpaired Image Translation with a Shared Rectified Flow

arXiv:2608.06784v1 Announce Type: new Abstract: Bidirectional unpaired image translation must preserve source-specific structure while learning coherent transformations in both directions without pair

Vernata: Self-Supervised Learning of LiDAR Point Representations

arXiv:2608.06919v1 Announce Type: new Abstract: LiDAR serves as a primary sensing modality for robots operating in outdoor environments. However, the performance of deep learning models in this domain

Walkable to Whom? Capturing Subjective Variability in Walkability Perception Using Multimodal Deep Learning

arXiv:2608.06934v1 Announce Type: cross Abstract: Visual perception of walkability varies substantially across individuals, reflecting differences in personal characteristics, experiences, and prefere

When Coordination Becomes a Threat: Communication Attacks in LLM-Controlled Multi-Robot Systems

arXiv:2608.06830v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used as high-level planners in embodied multi-robot systems, enabling robots to interpret natural language

agentsarxiv-cs-ro

When Semantics Saturate or Emerge: Adaptation-Conditional Semantic Utility in Source-Free Cross-Domain Few-Shot Learning

arXiv:2608.06673v1 Announce Type: new Abstract: Language descriptions in source-free cross-domain few-shot learning (SF-CDFSL) are often selected according to zero-shot accuracy obtained with a frozen

~45% lower MiniMax H3 sampler time with new Spectrum settings — degree 1 works surprisingly well (v0.1.8)

model-releasesr-stablediffusion

Follow-up to my original Spectrum MiniMax H3 post: https://www.reddit.com/r/StableDiffusion/comments/1vf1ze3/spectrum_acceleration_for_minimax_h3_in_comfyui/ In that first post, I released the MiniMax

A Bridge from Audio to Video: Phoneme-Viseme Alignment Allows Every Face to Speak Multiple Languages

arXiv:2510.06612v2 Announce Type: replace Abstract: Speech-driven talking face synthesis (TFS) focuses on generating lifelike facial animations from speech input. Current TFS models perform well in En

safetyarxiv-cs-cv

A Foundational EDM2-Based Generative Model for High-Resolution Synthetic Fetal Ultrasound Imaging from Open Datasets

arXiv:2608.05471v1 Announce Type: cross Abstract: Prenatal ultrasound imaging is key for assessing fetal health, but AI progress is limited by scarce, privacy-restricted, and hard-to-annotate datasets

Tutorials

A lot of the questions we get from developers are about the concepts behind the API: TTFT, context windows, sampling, fine-tuning, quantizat…

A lot of the questions we get from developers are about the concepts behind the API: TTFT, context windows, sampling, fine-tuning, quantization, deployment tradeoffs. We added Learn to the Together do

tutorialstogether-ai--x

A Low-Power Wearable Respiratory Sensor for Non-Invasive Stress Monitoring

arXiv:2608.05697v1 Announce Type: cross Abstract: Respiration provides a continuously available window into physiological state and behavior. However, monitoring it outside controlled settings remains

researcharxiv-cs-lg

A Multi-Layer System for Ultra-High-Resolution Static 360-Degree Telepresence

arXiv:2608.05570v1 Announce Type: cross Abstract: 360-degree video telepresence offers strong immersive potential but remains constrained by the limited resolution of current capture and display hardw

A Paragraph is Worth a Thousand Captions: Rethinking Text Supervision for Vision-Language Retrieval

model-releasesarxiv-cs-cv

arXiv:2608.05260v1 Announce Type: new Abstract: Contrastive vision-language models such as CLIP and BLIP are typically trained on short image captions, limiting their ability to retrieve images from d

A Reverse-BSDE Diffusion Sampler

arXiv:2505.06800v2 Announce Type: replace-cross Abstract: Diffusion-based generative models have renewed interest in stochastic differential equation methods for sampling from complex distributions. W

researcharxiv-cs-lg

A Six-Dimensional Taxonomy of Post-Training Adaptation Techniques with Applications in AI Governance

model-releasesarxiv-cs-lg

arXiv:2608.06246v1 Announce Type: new Abstract: Post-training adaptation has become central to modern machine learning practice and includes techniques such as retraining, fine-tuning, parameter-effic

ABC: Numerical Data Collection under Local Differential Privacy without Prior Knowledge

arXiv:2608.05737v1 Announce Type: cross Abstract: Local Differential Privacy (LDP) provides strong privacy guarantees for collecting numerical data. A fundamental challenge, however, is that existing

Local Ai

Activity Frames: Deterministic Screen-Activity Compilation for Agent Memory and Replay

arXiv:2608.05784v1 Announce Type: new Abstract: Computer-use agents pay full frontier inference to re-derive routines their user has already performed, because an agent's memory today records what the

local-aiarxiv-cs-ai

Adaptive Arena-based Contestable Argumentative Network-of-Experts for Open-Ended Care Plan Coordination

arXiv:2608.05391v1 Announce Type: new Abstract: Care plan coordination demands synthesizing heterogeneous clinical, functional, and psychosocial information across multiple professional disciplines, w

AegisShield: Democratizing Cyber Threat Modeling with Generative AI

arXiv:2509.10482v2 Announce Type: replace-cross Abstract: The increasing sophistication of technology systems makes traditional threat modeling hard to scale, especially for small organizations with l

Agentic self-driving microscopy benchmarks support qualification but do not necessarily generalize to unseen tasks

arXiv:2608.05266v1 Announce Type: new Abstract: Large language model agents are increasingly being developed to control a wide range of scientific characterization tools including microscopes and sync

Agentic Software Issue Resolution with Large Language Models: A Survey

arXiv:2512.22256v2 Announce Type: replace-cross Abstract: Software issue resolution aims to address real-world issues in software repositories based on natural language descriptions provided by users,

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning

arXiv:2608.05987v1 Announce Type: new Abstract: Reinforcement learning (RL) with verifiable rewards constructs trajectory-level advantage estimates, yet it often fails to credit the few pivotal decisi

AI Playing Business Games: Benchmarking Large Language Models on Managerial Decision-Making in Dynamic Simulations

arXiv:2509.26331v2 Announce Type: replace Abstract: The rapid advancement of LLMs sparked significant interest in their potential to augment or automate managerial functions. One of the most recent tr

Tutorials

ALTER: Modeling Longitudinal Changes via Regional Differencing for 3D CT Report Generation

arXiv:2608.05615v1 Announce Type: new Abstract: Computed tomography (CT) is widely used for clinical diagnosis and longitudinal follow-up, yet automatically generating accurate and complete radiology

tutorialsarxiv-cs-cv

An Early Warning of Emerging Biosecurity Risks in Frontier LLMs

model-releasesarxiv-cs-cl

arXiv:2607.18056v2 Announce Type: replace Abstract: Frontier large language models (LLMs) are increasingly integrated into scientific workflows, yet their growing biological capabilities may outpace c

AppDeltaWorld: Transition-Grounded Delta Code World Model for Mobile GUI Agents

arXiv:2608.05891v1 Announce Type: new Abstract: Mobile GUI agents can operate apps through pixel perception and touch actions, making them a promising interface for collecting and improving long-horiz

APQF: Agentic Profiling-Guided Structured Pruning and Mixed-Precision Quantization with Adaptive Fine-Tuning

arXiv:2608.05499v1 Announce Type: cross Abstract: Modern deep neural networks achieve strong performance, but their scale makes them costly and slow, especially on resource-constrained edge devices. P

ASAT: Adaptive Scoring and Thresholding with Human Feedback for Robust Out-of-Distribution Detection

arXiv:2505.02299v2 Announce Type: replace-cross Abstract: Machine Learning (ML) models are trained on in-distribution (ID) data but often encounter out-of-distribution (OOD) inputs during deployment--

At Black Hat, OpenAI reconstructs the OpenAI-Hugging Face incident and examines its implications for AI security, cyber resilience, and alignment (Black Hat on YouTube)

Black Hat on YouTube: At Black Hat, OpenAI reconstructs the OpenAI-Hugging Face incident and examines its implications for AI security, cyber resilience, and alignment — The ‘Breaking’ News: The OpenA

safetytechmeme

Autonomous Learning From Success and Failure: Goal-Conditioned Supervised Learning with Negative Feedback

arXiv:2509.03206v2 Announce Type: replace-cross Abstract: Learning from reward functions and imitation learning of demonstrations are the two principal approaches for training autonomous systems that

Autonomous Research Agents: A Survey of AI Scientists and the Verification Gap

arXiv:2608.05179v1 Announce Type: cross Abstract: Large language model (LLM) agents are increasingly used across the scientific research lifecycle: ideation, literature search, experiment design and e

BaKron: Efficient Quantization with Kronecker-Factored Hessians

arXiv:2608.06291v1 Announce Type: cross Abstract: We accelerate a family of algorithms for neural network quantization whose geometry is informed by any Kronecker-factored approximation of the Hessian

Basically every remaining good AI benchmark score has an implied asterisk next to it which reads: * could be signficantly higher with a bett…

model-releasesethan-mollick--x

On August 7, 2026 Ethan Mollick tweeted that “every remaining good AI benchmark score has an implied asterisk next to it which reads: * could be significantly higher with a better harness.” The commen

Bayesian adaptively-weighted ensembles for few-shot abdominal segmentation

arXiv:2608.05815v1 Announce Type: new Abstract: Few-shot learning has emerged as a promising approach for anatomical segmentation when labelled data are scarce. However, different few-shot learning al

Bayesian Expected Uncertainty Reduction (B-EUR) Model: A Computational Account of What Makes Design Options Worth Trying

arXiv:2608.05642v1 Announce Type: new Abstract: This paper proposes the Bayesian Expected Uncertainty Reduction (B-EUR) model, which formalizes the value of trying a candidate design action as its exp

Behavioral Residualization for Unsupervised Intrusion Detection in Automotive CAN Networks

arXiv:2608.05548v1 Announce Type: cross Abstract: Modern vehicles rely on the Controller Area Network (CAN) bus, whose design prioritizes low cost and real-time performance but provides no message aut

researcharxiv-cs-lg

Beyond Weights and Gradients: A Taxonomy of Federated Learning Messages

arXiv:2606.16891v2 Announce Type: replace-cross Abstract: Federated Learning is rapidly evolving beyond the exchange of traditional model weights and gradients, yet existing definitions fail to captur

Tutorials

BioM-JEPA: joint-embedding prediction of graph-connected gene blocks in single cells

arXiv:2608.05928v1 Announce Type: new Abstract: Single-cell transcriptomes are sparse observations of coordinated biological programmes, yet most self-supervised models learn by reconstructing individ

tutorialsarxiv-cs-lg

BlockPython: A Process-Aware Agent-Supported Platform for the Transition from Block-Based to Python Programming

arXiv:2608.05716v1 Announce Type: new Abstract: The transition from block-based to text-based programming requires learners to convert visible program structures into abstract textual expressions, whi

Can Open-Weight LLMs Produce Kernel-Verified Coq Proofs? A Pilot Study

model-releasesarxiv-cs-lg

arXiv:2608.05420v1 Announce Type: cross Abstract: Large language models (LLMs) can generate text that resembles a mathematical proof, but resemblance does not establish correctness. A formal proof che

ChainClaw: A Layered Agent Framework for Reliable On-Chain Execution

arXiv:2608.05790v1 Announce Type: new Abstract: General-purpose large language model agents have achieved strong performance on tool-augmented tasks, yet they rely on assumptions break down in blockch

CircuitSteer: Geometrically Aligned Multi-Layer Steering via Sparse Autoencoder Circuits

arXiv:2608.05732v1 Announce Type: new Abstract: Controlling the behavior of large language models (LLMs) remains a critical challenge for AI alignment. Existing steering methods, such as Contrastive A

safetyarxiv-cs-lg

CNM-BERT: A Drop-In Structural Embedding for Chinese Characters via Ideographic Description Sequences

model-releasesarxiv-cs-cl

arXiv:2608.05167v1 Announce Type: new Abstract: Token-based encoders like BERT treat Chinese characters as atomic identifiers, ignoring their recursive orthographic structure. Consequently, models rel

CoCo: Code as CoT for Text-to-Image Preview and Rare Concept Generation

arXiv:2603.08652v2 Announce Type: replace Abstract: Recent advancements in Unified Multimodal Models (UMMs) have significantly advanced text-to-image (T2I) generation, particularly through the integra