Search: “evaluation”

ImbalancE: Inference-Time Latent Search Against Degree Imbalance in Link Prediction

arXiv:2609.36996v1 Announce Type: new Abstract: Knowledge Graph Embedding models have been extensively used to learn representations of entities and relations in Knowledge Graphs for predicting missin

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Agents

In-Context Learning for Robots: Methods and Applications

DGX agent

arXiv:2609.36012v1 Announce Type: new Abstract: General-purpose robots must infer what a new task requires and translate that understanding into appropriate physical action. In-context learning (ICL)

agentsarxiv-cs-ro

30 Sept 2026

Inducing Process Supervision from Outcome-Only Reinforcement Learning

arXiv:2609.36641v1 Announce Type: cross Abstract: Process reward models (PRMs) have become a key component for LLMs, as their step-level feedback supports both post-training and test-time reasoning. H

IronLLM: Forging Compact Edge-Native Language Models for Real-Time Embodied Intelligence

arXiv:2609.36860v1 Announce Type: new Abstract: We present IronLLM-0.6B, a 654M-parameter language model designed for efficient on-device inference. IronLLM-0.6B combines a hybrid attention architectu

Is Agent Code Less Maintainable Than Human Code?

arXiv:2606.21804v2 Announce Type: replace-cross Abstract: Maintainability is a core dimension of software engineering, shaping how code is written, reviewed, and developed over time. While coding agen

agentsarxiv-cs-ai

Is Human-Readable Text Necessary for Effective LLM Fine-Tuning?

arXiv:2609.35868v1 Announce Type: new Abstract: Is human readability necessary for effective fine-tuning of large language models? We investigate whether model-conditioned training representations can

It's All Training: A Fully Synthetic Single-Stage Recipe for LLMs

arXiv:2609.37891v1 Announce Type: new Abstract: Current pre-training datasets are derived from web crawls, with all their issues, and were not designed to support mid- and post-training pipelines--for

researcharxiv-cs-cl

It's Not What the Image Shows: Irrelevant Context Destabilises VLM Judges Without Informing Them

arXiv:2609.37863v1 Announce Type: cross Abstract: Vision-language models (VLMs) are increasingly used in place of human annotators, making it important that substitutability tests reflect the model ra

researcharxiv-cs-ai

JointEdit3D: Feed-Forward 3D Scene Editing in a Unified Latent Space

model-releasesarxiv-cs-cv

arXiv:2606.13345v2 Announce Type: replace Abstract: Existing 3D scene editing methods typically rely on per-scene optimization over explicit 3D representations or cascaded edit-and-reconstruct pipelin

Tutorials

JudgeCast: Time Series Forecasting with Experience-Informed Covariate Judgements

arXiv:2609.36966v1 Announce Type: cross Abstract: Covariate effects vary across contexts and shift over time, requiring forecasters to assess how to use them for each forecasting context. As forecasti

tutorialsarxiv-cs-ai

Kinematic Nonlinear Spatio-Temporal Trajectory Warping for Contact-Rich Dexterous Manipulation Demonstrations

arXiv:2609.36676v1 Announce Type: new Abstract: We present a straightforward but effective method for repurposing existing contact-rich dexterous manipulation demonstrations. Starting from inputs of h

researcharxiv-cs-ro

Kolmogorov-Arnold Classifier Systems as Universal Approximators

model-releasesarxiv-cs-lg

arXiv:2609.37958v1 Announce Type: new Abstract: As the input dimension n grows, rule-based machine learning, such as Learning Classifier Systems (LCSs), faces a fundamental scalability bottleneck for

Local Ai

KV-Kaizen: Learning Context-Adaptive Cache Compression Choices

arXiv:2609.37988v1 Announce Type: new Abstract: As the context size of text processed with an LLM grows, the size of KV caches can outstrip the memory allocated for the original model weights. This im

local-aiarxiv-cs-ai

Hardware

Label Less, Learn More: Resource-Efficient Active Semi-Supervised Learning for Onboard Satellite Image Annotation

arXiv:2609.37481v1 Announce Type: new Abstract: Large-scale pervasive sensing increasingly relies on high-resolution satellite imagery, yet task-specific onboard vision is constrained by costly annota

hardwarearxiv-cs-cv

Language as the Interface: Foundation-Model Contrastive Learning Links Transcriptomes and Electrophysiology

arXiv:2609.37024v1 Announce Type: new Abstract: Integrating transcriptomic and electrophysiological data is essential for building multimodal foundation models for neuroscience. Patch-seq provides pai

Large Language Models Exhibit Human-Like Bayesian Hypocrisy

arXiv:2609.35779v1 Announce Type: cross Abstract: Given recent achievements of large language models (LLMs), frontier models are expected to perform well on Bayesian reasoning tasks, at least as well

Large-scale factor analysis shows machine intelligence is only partially interpretable

arXiv:2609.36515v1 Announce Type: cross Abstract: A common assumption in language model development is that cognitive abilities are organized around a general, domain-free intelligence factor, like fl

Learn from the Gap: Differential-Aware Advantage Pruning with Adaptive Rollout Sampling for GRPO

arXiv:2609.36932v1 Announce Type: new Abstract: Recently, Group Relative Policy Optimization (GRPO) and its variants have been developed for policy optimization and demonstrated notable performance ga

Applications

Learning from Shared-Control Overrides: Context-Driven Acceleration Profile Prediction for Personalized Overtaking

arXiv:2609.37684v1 Announce Type: new Abstract: Adaptive Cruise Control (ACC) systems are typically calibrated for an average driver, often resulting in a mismatch between vehicle behavior and individ

applicationsarxiv-cs-ai

Learning from Teacher Continuations at Student States

arXiv:2609.36246v1 Announce Type: new Abstract: We present OLIVE (OnLine InterVEntion). At each iteration, the evolving student policy generates a new prefix, the teacher continues it autoregressively

Tutorials

Learning Samples Importance: Parameterizing Dual Variables in Everywhere Learning

arXiv:2609.36310v1 Announce Type: new Abstract: Everywhere learning provides a principled framework for training AI models under constraints that must hold throughout the data distribution. In the dua

tutorialsarxiv-cs-lg

Tutorials

LeRF: Learning Reference Coordinate Frames for Perspective Taking Reasoning

arXiv:2609.36219v1 Announce Type: new Abstract: Perspective taking is a fundamental component of spatial intelligence, requiring models interpret spatial relations from a specified viewpoint, such as

tutorialsarxiv-cs-cv

LLM Judge Validation Under Sparse Overlap: From Inference to Design

arXiv:2609.31857v2 Announce Type: replace Abstract: Validating an LLM-as-a-judge requires estimating its agreement with humans, yet annotation budgets rarely allow every item to be multiply labeled. W

researcharxiv-cs-ai

LLMs Learn to Evade Latent Monitors from Prior Feedback Alone

arXiv:2609.36490v1 Announce Type: cross Abstract: Latent space monitors aim to detect undesired behaviors in LLM agents by inspecting an agent's internal activations rather than its outputs. However,

agentsarxiv-cs-ai

LongSpark: Efficient speculative decoding with a fixed-cost parallel drafter

arXiv:2609.37029v1 Announce Type: cross Abstract: Speculative decoding accelerates autoregressive inference by verifying multiple draft tokens in a single target forward pass. However, as the context

researcharxiv-cs-ai

Lookahead-R: Budget-Aware Tool Retrieval via Execution-Centric Planning

arXiv:2609.35811v1 Announce Type: cross Abstract: Tool retrieval is a critical bottleneck for LLM-based agents operating over large, heterogeneous API ecosystems. Existing approaches face an inherent

Looped Actor: Depth-Recurrent Reasoning Models for Reinforcement Learning

arXiv:2609.37432v1 Announce Type: new Abstract: Looped reasoning models repeatedly apply a shared set of parameters, enabling more computation without increasing the model size. These models also supp

safetyarxiv-cs-lg

Losing the name before the box: measuring and repairing what narrow fine-tuning costs a detector outside its deployment vocabulary

arXiv:2609.36426v1 Announce Type: cross Abstract: A detector pretrained on a broad corpus is fine-tuned on a narrow domain, its in-domain accuracy improves, and it ships. We ask what happens meanwhile

researcharxiv-cs-cv

Lost in Translation: Measuring the Effect of Non-Native English on End User Performance of Large Language Models

arXiv:2609.36214v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used by people whose first language is not English, yet these users have been shown to receive systematica

researcharxiv-cs-cl

Lucid Dreaming for World Models: Learning to Doubt Imagination and Decide by Trust

arXiv:2609.37156v1 Announce Type: cross Abstract: World models enable agents to learn and plan in imagination, but predictions beyond their experience can become unreliable and mislead decisions. Exis

Making Analog Training Scale: Co-Designing Mapping, Optimizer, and Converters

model-releasesarxiv-cs-lg

arXiv:2609.36584v1 Announce Type: new Abstract: Analog in-memory computing (AIMC) offers an alternative for model training by executing matrix operations directly where weights are stored. However, sc

Making Duplicate Reimbursement Unrepresentable: A Verified Ethereum E-Invoice System for Humans and AI Agents

arXiv:2609.37819v1 Announce Type: cross Abstract: Electronic invoices are replacing paper invoices worldwide, but today's centralized architectures leave three problems unsolved on the consumption sid

MAPLE: Medical Aspect-Based Summarization with Phrase-Level Evidence

arXiv:2601.03418v3 Announce Type: replace Abstract: Trustworthy clinical summarization requires every claim to be traceable to its evidence, yet existing attribution often resolves only to the sentenc

Med-RADIO: Reducing All Medical Domains Into One via Multi-Teacher Distillation

arXiv:2609.37682v1 Announce Type: new Abstract: The rapid expansion of large-scale medical datasets and computational resources has driven significant progress in medical foundation models. Given the

researcharxiv-cs-cv

MERGE: Multi-LLM Ensemble for Retrieval via Generative Enrichment

arXiv:2609.37574v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used to enrich user queries in information retrieval (IR) so that a standard retriever such as BM25 can

Message Passing Does More with Less for In-Context Learning on Graphs

arXiv:2609.37057v1 Announce Type: new Abstract: Achieving strong performance with graph neural networks (GNNs) typically requires training and hyperparameter tuning for each dataset, incurring repeate

researcharxiv-cs-lg

Meta-SecAlign: Training LLMs against Prompt Injection for Robust Agents

arXiv:2507.02735v4 Announce Type: replace-cross Abstract: Prompt injection attacks, where untrusted data contains an injected prompt to manipulate the system, have been listed as the top security thre

Mirror-Score: Calibrated, Inference-only Scoring Exposes the Limits of Sequence-compatibility Ranking in D-peptide Design

arXiv:2609.36057v1 Announce Type: new Abstract: D-peptides combine protease resistance with high target specificity, but computational design of D-peptide binders remains immature. Mirror-Peptidizer i

Mixture of Self-Improving Branches For Agent Harness Optimization

arXiv:2609.37834v1 Announce Type: new Abstract: Harness optimization provides a practical setting for recursive self-improvement (RSI), where agent-generated modifications inform subsequent changes th

MLToolBench: Learning Tool-Augmented Agents for Machine Learning Development

arXiv:2609.36679v1 Announce Type: new Abstract: Machine learning engineering (MLE) agents have made substantial progress, but learning through ML experimentation remains costly in time and computation

agentsarxiv-cs-ai

Mnemon: Raw Records, Fast Judgments, Slow Thoughts

arXiv:2609.36059v1 Announce Type: cross Abstract: Long-term memory lets an LLM assistant use a history it can no longer reread, and most memory systems build it by rewriting conversations into facts,

Local Ai

MoCA-Video: Motion-Aware Concept Alignment for Consistent Video Editing

arXiv:2506.01004v3 Announce Type: replace-cross Abstract: Unlike traditional video editing or inpainting, video semantic mixing fuses a reference concept with a moving target entity to produce a hybri

local-aiarxiv-cs-ai

Momentum-Coupled Rubric Adaptation for Detailed Image Captioning

arXiv:2609.36893v1 Announce Type: new Abstract: Detailed image captioning requires accurate and comprehensive descriptions of fine-grained visual content, yet caption quality spans factual accuracy, i

MotorMind: Scaffolding General Vision Language Models for Zero-Shot Robot Manipulation

arXiv:2609.38078v1 Announce Type: new Abstract: Vision-language-action (VLA) models have advanced robotic manipulation, but their zero-shot generalization in new tasks and environments remains limited

safetyarxiv-cs-ro

Moving Object Detection from Moving Camera Using Focus of Expansion Likelihood and Segmentation

arXiv:2507.13628v3 Announce Type: replace Abstract: Separating moving and static objects from a moving camera viewpoint is essential for 3D reconstruction, autonomous navigation, and scene understandi

agentsarxiv-cs-cv

MSTypography: Multi-character Semantic Typography via Balancing Word Legibility and Object Recognizability

arXiv:2609.37141v1 Announce Type: new Abstract: Semantic typography is a design technique where the visual representation of a word conveys its semantic meaning, while maintaining its legibility. Exis

researcharxiv-cs-cv

Multi-Granularity Language-Guided Imitation Learning via Instruction Decomposition

arXiv:2609.37135v1 Announce Type: new Abstract: Using language instructions as conditions to guide robot policy learning has recently become an important research domain. However, existing language-gu

safetyarxiv-cs-cv

Applications

Multi-Site Real-World Performance of Commercial AI for Pulmonary and Incidental Pulmonary Embolism Detection

arXiv:2609.37750v1 Announce Type: cross Abstract: Pulmonary embolism (PE) is a leading cause of cardiovascular mortality, yet the real-world performance of FDA-cleared AI detection models remains inco

applicationsarxiv-cs-ai