Search: “evaluation”

Natural Language to First-Order Logic LLM-based Autoformalization

arXiv:2610.12030v1 Announce Type: new Abstract: Large Language Models (LLMs) have renewed interest in autoformalization. Yet, when First-Order Logic (FOL) is considered as the target formalism, the fi

researcharxiv-cs-cl

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Parametric Trajectory Distillation for Few-Step Video Generation

DGX agent

arXiv:2610.11498v1 Announce Type: new Abstract: Video diffusion and flow models require many sequential evaluations, making generation computationally expensive. Few-step distillation reduces this cos

tutorialsarxiv-cs-cv

9 Oct 2026

PathLang: A Language-Centered Benchmark for Vision-Language Models in Computational Pathology

arXiv:2610.11329v1 Announce Type: new Abstract: Pathology vision-language models (VLMs) have shown strong visual perception ability, but their robustness in the language domain remains poorly characte

Recursive Self-Improvement through Multi-Agent Self-Supervision

arXiv:2610.12176v1 Announce Type: new Abstract: Recursive self-improvement (RSI) of a model on non-verifiable tasks, such as open-ended research, faces a supervision bottleneck when its outputs exceed

agentsarxiv-cs-ai

ReSI: Recursive Safety Improvement toward Resistant and Resilient AI

model-releasesarxiv-cs-ai

arXiv:2610.12233v1 Announce Type: cross Abstract: Recursive self-improvement, the participation of AI systems in improving their own capabilities, is beginning to move from theoretical prospect to pra

Scalable LEO Conjunction Screening using Adaptive Synthetic-Covariance Thresholds

arXiv:2610.11645v1 Announce Type: new Abstract: As orbital populations grow, conjunction screening must search more object pairs for potential collision risks. Existing pipelines use early-stage filte

researcharxiv-cs-ro

Applications

Seed2Scale: A Self-Evolving Data Engine with Parallel Worlds Expansion for Scalable Robot Learning

arXiv:2603.08260v2 Announce Type: replace Abstract: Existing data generation methods for robot learning suffer from limited exploration, embodiment gaps, low signal-to-noise ratios, and domain shifts,

applicationsarxiv-cs-ro

Synthesis Through Simulation: Generating Coherent Enterprise Data via Scalable Agent-System Interaction

arXiv:2610.10549v1 Announce Type: new Abstract: Tool-calling agents have become central to enterprise AI, yet training and evaluating them at scale remains severely constrained due to business and leg

safetyarxiv-cs-ai

Tutorials

Thinking Inertia: LLMs Keep Thinking When Told Not To

arXiv:2610.11765v1 Announce Type: new Abstract: Large Language Models (LLMs) increasingly ship with explicit 'thinking modes', yet their counterpart, 'no-thinking', has received far less attention. We

tutorialsarxiv-cs-cl

TKCAM: Text and Keyframe to Camera Trajectory Generation

arXiv:2610.11105v1 Announce Type: new Abstract: Generating high-quality and controllable camera motion is essential for AI-assisted cinematography, video synthesis, and 3D scene understanding. We intr

When History Helps and Hurts: Selective History Use across Multimodal Turns

arXiv:2610.11948v1 Announce Type: new Abstract: Reliable multimodal interaction depends on selective use of conversational history: an earlier question may remain relevant while its previous answer is

WorldFact-Bench: Beyond Image-Internal Plausibility to Image-World Consistency

arXiv:2610.11184v1 Announce Type: new Abstract: Advances in image generation have made visual authenticity increasingly difficult to assess. Although image forensics now examines both generation artif

A Multi-Source Ultrasound Benchmark Revealing the Limits of Contemporary Self-Supervised Anomaly Detection Methods

arXiv:2610.09677v1 Announce Type: new Abstract: Self-supervised anomaly detection is a promising paradigm for medical ultrasound, as normal images are often easier to obtain than exhaustive annotation

AdSpark: A Large-Scale Dataset and Benchmark for Product-Centric Advertisement Video Generation

arXiv:2610.10047v1 Announce Type: new Abstract: Product-centric advertisement video generation aims to create promotional videos that preserve fine-grained product identity while presenting selling po

Adversarial Images Hijack Web Agents from Visual Grounding to Browser Execution

arXiv:2610.09240v1 Announce Type: cross Abstract: Modern web agents built on large vision-language models process webpages, select relevant UI elements, and translate model outputs into browser action

Local Ai

AeroEval: Staged Program and Execution Validation for AI-Generated Drone Missions

arXiv:2610.09764v1 Announce Type: new Abstract: Large Language Models (LLMs) can generate drone programs from natural-language mission descriptions, but syntactically valid programs may still violate

local-aiarxiv-cs-ro

Causal Posterior Estimation

model-releasesarxiv-cs-lg

arXiv:2505.21468v2 Announce Type: replace Abstract: We present Causal Posterior Estimation (CPE), a novel method for Bayesian inference in simulator models, where evaluating the likelihood function is

Conditional Accuracy Profiles: Diagnosing LLM Judges across Deployment Conditions

model-releasesarxiv-cs-lg

arXiv:2610.09229v1 Announce Type: new Abstract: LLM-as-judge is now a standard tool for scalable evaluation, but judge performance is still often summarized by a single accuracy number. This aggregate

Constraint Tree Exploration for Learning from Language Feedback

arXiv:2610.09107v1 Announce Type: cross Abstract: Natural-language feedback in interactive learning often explains why an action failed by pointing to violated requirements. Misinterpreting this feedb

agentsarxiv-cs-cl

Detecting Adversarial Images through Response Profiles of Vision-Language Models

arXiv:2610.10436v1 Announce Type: new Abstract: Adversarial perturbations can alter the predictions of frozen vision-language models (VLMs) while leaving their confidence and image--text similarity pa

researcharxiv-cs-cv

Dialect-Robust Speech Language Models with Synthetic Pseudo-Dialect Augmentation

arXiv:2610.09321v1 Announce Type: new Abstract: Speech Language Model (SLM) performance often degrades on dialects due to data scarcity. Conventional text-to-speech (TTS) augmentation struggles to cov

researcharxiv-cs-cl

Environmental Change Detection for Real-World Change Analysis

arXiv:2506.11481v2 Announce Type: replace Abstract: Scene Change Detection (SCD) evaluates changes using predefined query-reference (i.e., present-past) image pairs. However, this formulation overlook

Epistemic Policy Divergence in Multi-Turn LLM Contamination: A Protocol-Gradient Investigation

arXiv:2609.35308v2 Announce Type: replace Abstract: Large language models treat conversation history as unverified context, so false premises injected into prior turns can be adopted as fact, a failur

Estimating Model-Level Membership Inference Vulnerability Without Reference Models

arXiv:2510.19773v2 Announce Type: replace Abstract: Membership inference attacks (MIAs) have emerged as the standard tool for evaluating the privacy risks of AI models. However, state-of-the-art attac

researcharxiv-cs-lg

GraphRectify: Graph-Based Transfer of Adversarial Example Detectors Across Neural Networks

arXiv:2610.10423v1 Announce Type: new Abstract: Adversarial example detectors are often tied to the classifier backbone they were trained on, limiting reuse when the protected model is replaced or upg

researcharxiv-cs-cv

Homogenization in Multi-Agent Systems

arXiv:2610.09824v1 Announce Type: new Abstract: Multi-agent systems (MAS) leverage interactions between agents to perform complex tasks. Despite their success, we show that these interactions can also

agentsarxiv-cs-lg

How to train your model organism

model-releasesarxiv-cs-lg

arXiv:2610.10203v1 Announce Type: new Abstract: Model organisms of alignment-relevant behaviors (e.g., backdoors, sycophancy, spurious correlations) have emerged as a key tool for evaluating whitebox

Applications

KASALv2: Fully Automatic 3D Rotational Symmetry Classification and Axis Localization

arXiv:2610.09534v1 Announce Type: new Abstract: Rotational symmetry is an important prior in 6D pose estimation, improving pose accuracy and supporting symmetry-aware evaluation. However, current symm

applicationsarxiv-cs-cv

LRCC: Generalizing Low-Rank Compression with Conditional Computation

arXiv:2610.08858v1 Announce Type: new Abstract: Low-rank compression reduces the cost of pretrained language models by replacing linear transformations with low-rank factorizations. However, conventio

MIRROR: From Imitation to Internalization in LLM Personalization

arXiv:2610.09795v1 Announce Type: new Abstract: The demand for personalized LLMs is shifting from style imitation toward content quality. We investigate whether self-distillation can bridge this gap i

safetyarxiv-cs-cl

Multi-Objective Aligned Small Language Model Framework for SUD Patient Dialogue Generation

arXiv:2610.09209v1 Announce Type: new Abstract: Substance Use Disorder (SUD) counseling requires patient responses that reflect underlying cognitive states such as beliefs, coping strategies, and read

safetyarxiv-cs-cl

Phoneme-Guided Initialization for LLM-based Speech Recognition

arXiv:2610.08994v1 Announce Type: cross Abstract: Speech large language models (speech LLMs) perform well on automatic speech recognition (ASR) when sufficient paired speech-text data is available, bu

researcharxiv-cs-cl

ScribbleEdit: A Benchmark for Scribble-Only Image Editing

arXiv:2610.09382v1 Announce Type: cross Abstract: Scribble-based interaction provides a lightweight and intuitive way for users to specify image editing intents in interactive editing tools. However,

SemanticFold: Latent Sequence Compression SeparatesLanguage Modeling, Decodability, and Reasoning

arXiv:2610.10304v1 Announce Type: cross Abstract: We study whether latent sequence compression of prompt prefixes preserves the capabilities that large language models rely on during inference. We int

Local Ai

The Persona Hierarchy Model: Understanding Contextual Generalization in Fine-Tuning LLMs

arXiv:2610.09384v1 Announce Type: new Abstract: Language models are routinely fine-tuned under a fixed context, such as a generic system prompt, persona or domain-specific instruction, yet the learned

local-aiarxiv-cs-cl

VideoZeroBench: Probing the Limits of Video MLLMs with Spatio-Temporal Evidence Verification

arXiv:2604.01569v2 Announce Type: replace Abstract: Video multimodal large language models achieve strong results on existing benchmarks, but answer accuracy alone does not establish whether they can

When Forgetting Looks Like Improvement: Metric Masking in Streaming Diarizer Adaptation and the Price of Rehearsal

arXiv:2610.08828v1 Announce Type: new Abstract: Small-data adaptation can improve speech detection while degrading speaker attribution. We study this discrepancy in a released streaming diarizer adapt

A BEMD-Based Quaternion Filtering Approach Sharp-to-Soft Kernel CT Image Conversion

arXiv:2610.07071v1 Announce Type: new Abstract: The quality of computed tomography (CT) images is significantly affected by the selection of reconstruction kernels: sharp kernels improve spatial resol

researcharxiv-cs-cv

A Validated Dataset and Benchmark for Coherent Multi-Diagram SysML Models

model-releasesarxiv-cs-ai

arXiv:2610.07356v1 Announce Type: cross Abstract: Systems engineers use several diagrams to describe the structure and behavior of systems. Engineers create these diagrams together to make sure that t

Agentic Design Space Exploration for Joint Hardware Configuration Selection and Mapping of AI Inference Workloads on Heterogeneous Edge SoCs

arXiv:2610.07191v1 Announce Type: cross Abstract: Modern edge Systems-on-Chip (SoCs) integrate heterogeneous processing units (PUs) such as CPUs, GPUs, and NPUs, each with distinct performance and ene

agentsarxiv-cs-ai

Artificial Hivemind: The Open-Ended Homogeneity of Language Models (and Beyond)

arXiv:2510.22954v2 Announce Type: replace Abstract: Language models (LMs) often struggle to generate diverse, human-like creative content, raising concerns about the long-term homogenization of human

safetyarxiv-cs-cl

Tutorials

AssemState: Manual and Physical-State-Guided Reasoning for Zero-shot Furniture Assembly

arXiv:2610.08446v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have made significant progress in visual understanding, but precise 3D spatial reasoning integrated with physic

tutorialsarxiv-cs-ai

Local Ai

ATLAS-AL: Adaptive Trust-Region for Latent Adversarial Searches via Active Learning

arXiv:2610.07323v1 Announce Type: cross Abstract: Security evaluation of learning-based systems requires more than just testing the system against a fixed collection of attacks. It requires adaptive m

local-aiarxiv-cs-cv

AVMeme Exam: A Multimodal Multilingual Multicultural Benchmark for LLMs' Contextual and Cultural Knowledge and Thinking

arXiv:2601.17645v2 Announce Type: replace-cross Abstract: Internet audio-visual clips convey meaning through time-varying sound and motion, which extend beyond what text alone can represent. To examin

Behavioral Safety Assessment towards Large-scale Deployment of Autonomous Vehicles, Part I: Methodology

arXiv:2610.08450v1 Announce Type: new Abstract: Autonomous vehicles (AVs) have significantly advanced in real-world deployment in recent years, yet safety continues to be a critical barrier to widespr

safetyarxiv-cs-ro

Beyond Corrected Memory: Execution Consistency in Multi-Agent Systems

model-releasesarxiv-cs-ai

arXiv:2610.08101v1 Announce Type: new Abstract: Shared memory coordinates agents' actions, but correct records do not establish that those actions satisfy task requirements. Memory governance and fail

Beyond Successor Accuracy: State Retention for Recursive Self-Improvement in Recommendation

arXiv:2610.07105v1 Announce Type: cross Abstract: Recommendation recursive self-improvement (Rec-RSI) feeds recommender outputs into subsequent training. Evaluating each round solely through its lates

researcharxiv-cs-ai

Calibrated Answers About Randomized Trials From a 4-Billion-Parameter Open Model: A Registered Test and a License-Clean Release

arXiv:2610.07019v1 Announce Type: new Abstract: Fiorillo v0.5 is an open model that answers typed questions with a probability for each answer. Its main specialist reads a randomized trial's article,