Search: “evaluation”

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

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Safety

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

DGX agent

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--

safetyarxiv-cs-ai

7 Aug 2026

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

safetyarxiv-cs-ai

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

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

CodeGrep: An RL-Trained Retrieval Agent for LLM Coding Agents

arXiv:2608.05886v1 Announce Type: cross Abstract: Modern LLM coding agents such as Claude Code and OpenHands share a common inefficiency: they spend much of their token budget finding the file to patc

Local Ai

CogVis: Must Open-Vocabulary Change Detection Perceive the Scene Anew for Every Query?

arXiv:2608.06150v1 Announce Type: new Abstract: Earth-surface monitoring requires change detection models capable of recognizing arbitrary semantic categories. Open-Vocabulary Change Detection (OVCD)

local-aiarxiv-cs-ai

Coherence-Oriented Dream Scene Visualisation

arXiv:2608.05233v1 Announce Type: new Abstract: Dreams can be emotionally intense but difficult to communicate. We describe the Dream Scene Visualiser (DSV) system which turns written dream descriptio

Local Ai

Communication-Aware Multi-Agent Reinforcement Learning for Decentralized Cooperative UAV Deployment

arXiv:2603.16141v2 Announce Type: replace-cross Abstract: Autonomous Unmanned Aerial Vehicle (UAV) swarms are increasingly used as rapidly deployable aerial relays and sensing platforms, yet practical

local-aiarxiv-cs-lg

Comparative Approaches to Agent Retrieval over Large Skill Libraries

arXiv:2608.06196v1 Announce Type: new Abstract: Agents backed by large skill libraries must decide which skills to load and in what order. Loading the entire library into context is expensive and prov

Confidence matters: Leveraging Multi-view Geometric Priors for GS-based Reconstruction

arXiv:2608.06117v1 Announce Type: new Abstract: 3D Gaussian splatting (3DGS) has emerged as a widely-used tool for novel view synthesis, offering real-time rendering in a sparse representation. Howeve

Constraint-First Reasoning: A Training-Free Protocol for Exploiting Answer-Space Constraints in Mathematical Problem Solving

arXiv:2608.05254v1 Announce Type: new Abstract: Large language models can derive a plausible mathematical object yet still violate explicit requirements--for example, by omitting a modular reduction,

researcharxiv-cs-cl

Coordinated Multi-Robot Disassembly for Makespan Optimization of Large-Scale Assemblies

arXiv:2608.05830v1 Announce Type: new Abstract: Multi-robot task and motion planning for disassembly tasks requires robots to operate in confined workspaces while coordinating their motions with other

researcharxiv-cs-ro

Counterfactual Analysis via Large Language Models

arXiv:2608.05367v1 Announce Type: new Abstract: Counterfactual analysis aims to predict potential outcomes under hypothetical scenarios, offering valuable insights for decision-making. This paper inve

CRINN: Contrastive Reinforcement Learning for Approximate Nearest Neighbor Search

arXiv:2508.02091v4 Announce Type: replace-cross Abstract: Approximate nearest-neighbor search (ANNS) algorithms have become increasingly critical for recent AI applications, particularly in retrieval-

Cross-Architecture Steering Transfer in Language Models: A Systematic Empirical Study

model-releasesarxiv-cs-cl

arXiv:2608.05164v1 Announce Type: new Abstract: Independently trained large language models may develop shared internal representations of semantic concepts despite architectural differences -- but wh

Local Ai

Curia-MAE: Multi-Modal Multi-Anatomy MAE Pre-Training for 3D Medical Image Segmentation

arXiv:2608.05844v1 Announce Type: new Abstract: Radiology foundation models learn transferable representations that can be adapted to new tasks by training only small layers on top of a frozen encoder

local-aiarxiv-cs-cv

d3LLM: Ultra-Fast Diffusion LLM using Pseudo-Trajectory Distillation

arXiv:2601.07568v3 Announce Type: replace-cross Abstract: Diffusion large language models (dLLMs) offer capabilities beyond those of autoregressive (AR) LLMs, such as parallel decoding and random-orde

Decolonizing Linguistic Policies in Automated Speech Recognition: A Framework for Cross-Culturally Competent Speech AI

arXiv:2608.06141v1 Announce Type: new Abstract: This paper focuses on automatic speech recognition (ASR) and ASR-mediated voice interfaces that shape access to public services, healthcare, and educati

safetyarxiv-cs-cl

DeepForgeSeal: Latent Space-Driven Semi-Fragile Watermarking for Deepfake Detection Using Adversarial Reinforcement Learning

arXiv:2511.04949v2 Announce Type: replace-cross Abstract: Rapid advances in generative AI have led to increasingly realistic deepfakes, posing growing challenges for law enforcement and public trust.

Diff-VF: Training-free High-quality Long Video Generation via Diffusion Model

arXiv:2608.05976v1 Announce Type: new Abstract: Recently, diffusion models have made great progress in video generation. However, most existing video diffusion models are trained with short videos, an

Different Perturbations, Different Mechanisms: Understanding Continued Pre-training for Zero-Shot Dialect Robustness

arXiv:2608.05510v1 Announce Type: new Abstract: Dialectal variation remains a major challenge for multilingual language models. Perturbation-based continued pre-training (CPT) has emerged as a promisi

safetyarxiv-cs-cl

Does FLAIR super-resolution erase or hallucinate small white-matter lesions?

arXiv:2608.06311v1 Announce Type: cross Abstract: White matter hyperintensities (WMH), bright regions on Fluid-attenuated Inversion Recovery (FLAIR) scans are associated with cerebrovascular pathology

DREAM: LLM-based Dynamic Role-playing via Event-Aware Memory Graph

arXiv:2608.05170v1 Announce Type: cross Abstract: Role-playing agents (RPAs) have emerged as a key application of large language models, enabling immersive and high-fidelity character simulation. Accu

Dual-Output Multi-Exposure HDR Reconstruction via SDR Fusion and Gain Map Inverse Tone Mapping

arXiv:2608.05626v1 Announce Type: new Abstract: We propose DOME-HDR, a dual-output multi-exposure HDR reconstruction framework that jointly produces a perceptually balanced SDR image and a consistent

DyPES-VLA: Learning Shared Dynamics Priors and Embodiment-Specific Control for Cross-Embodiment Manipulation

arXiv:2608.06374v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have become a powerful paradigm for robot manipulation, but training a single generalist policy for heterogeneous ro

safetyarxiv-cs-ro

Effective pruning of task-trained recurrent neural networks using noisy fluctuations and connection rescaling

model-releasesarxiv-cs-lg

arXiv:2608.05464v1 Announce Type: cross Abstract: The pruning of network connections is key to brain function but, despite its importance, there exist few biologically-plausible pruning rules with dem

EmoWorld: A Decoupled Affective Field for Controllable Emotional Video Generation

arXiv:2608.06231v1 Announce Type: new Abstract: Emotion shapes how viewers interpret a scene, yet existing video generators entangle global atmosphere, affect-bearing semantic cues, and temporal progr

safetyarxiv-cs-cv

EnvACE: Internalizing Environment Dynamics via World Rehearsal for Agentic Reinforcement Learning

arXiv:2608.06197v1 Announce Type: new Abstract: Training large language model agents for long-horizon tool use typically relies on interactions with real or synthesized executable environments, whose

safetyarxiv-cs-ai

Equation-Free Period-Aware Forecast-Error Contraction for Estimating Negative Largest Lyapunov Exponents from Short Trajectory Ensembles

model-releasesarxiv-cs-lg

arXiv:2608.05522v1 Announce Type: cross Abstract: Estimating positive largest Lyapunov exponents from data is comparatively natural because neighboring trajectories separate, whereas stable dynamics r

Equipment-centric workpiece localization in near real-time using deep learning-based vision and event-driven finite state machines

arXiv:2608.05744v1 Announce Type: new Abstract: Continuous workpiece localization is essential for traceability and process coordination in hot forging, but direct tracking is unreliable because of ex

researcharxiv-cs-lg

Evidential Rule Learning for Interpretable Classification with Abstention

arXiv:2608.05859v1 Announce Type: cross Abstract: Interpretable classification often requires more than accurate predictions for real-life deployment: models should be transparent about the evidence b

From Economic Agents to Agentic Economies: A Systems Blueprint for Economic World Models

arXiv:2608.06020v1 Announce Type: new Abstract: Economic World Models (EWMs) are generative economic models that simulate how economies evolve from within by modeling heterogeneous agents, their belie

safetyarxiv-cs-ai

GrandCode: Achieving Grandmaster Level in Competitive Programming via Agentic Reinforcement Learning

arXiv:2604.02721v3 Announce Type: replace Abstract: Competitive programming remains one of the last few human strongholds in coding against AI. The best AI system to date still underperforms the best

GROM: Gradient-Free Rapid One-Shot Machine Unlearning

arXiv:2608.05783v1 Announce Type: cross Abstract: Machine unlearning has become a critical capability for safely removing specific, sensitive knowledge from large language models (LLMs). Current state

GST-Bench: Can VLMs Develop Global Spatial Awareness from Video?

model-releasesarxiv-cs-cv

arXiv:2608.05747v1 Announce Type: new Abstract: Spatial intelligence is fundamental to embodied agents, yet existing benchmarks focus on local spatial perception from single or few viewpoints, overloo

Applications

Handling Missing Data in Probabilistic Regression Trees

arXiv:2608.06195v1 Announce Type: cross Abstract: Probabilistic Regression Trees (PRTrees) are a smooth and consistent alternative to classical regression trees, producing continuous predictions throu

applicationsarxiv-cs-lg