Search: “evaluation”

Benchmarking Vision-Language Models on Synapse Detection and Proofreading in Connectomics

arXiv:2609.36492v1 Announce Type: cross Abstract: We benchmarked vision-language models (VLMs) on the decisions annotators take when inspecting electron microscopy images in connectomics: synapse dete

researcharxiv-cs-ai

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Beyond Binary Preferences: Graded Preference Optimization for Limb-Motion Captioning

DGX agent

arXiv:2609.36628v1 Announce Type: new Abstract: Vision-Language Models (VLMs) can generate rich video captions, yet often misidentify which person performs an action or which limb is involved, particu

model-releasesarxiv-cs-cv

30 Sept 2026

Counterfactual Probing for Parallel Unmasking with Hidden Forest Structure

arXiv:2609.37841v1 Announce Type: new Abstract: Masked generative models offer parallel token prediction, but accurate parallel sampling must account for dependencies among tokens. When dependencies a

DecoyTrace: Toxic Decoys for Active Defense in Decentralized Federated Learning

arXiv:2609.36330v1 Announce Type: cross Abstract: Decentralized Federated Learning (DFL) eliminates the central aggregation server, reducing the single point of observation that traditional defenses a

Agents

DeepRewind: Predicting and Repairing Premature Commitments in Deep Research Agents

arXiv:2609.36344v1 Announce Type: new Abstract: Deep-research agents conduct long-horizon investigations through iterative search, evidence evaluation, belief revision, and synthesis. However, they ma

agentsarxiv-cs-cl

DispFlow-GS: Displacement Flow Supervision with Motion Disentangling for Monocular Deformable 3D Gaussian Splatting

arXiv:2609.36940v1 Announce Type: new Abstract: Accurate dynamic scene reconstruction is important for robotic perception, where temporally consistent representations of dynamic environments are essen

safetyarxiv-cs-cv

Do Agent Benchmarks Do What They Say? An Executable-Contract Audit of Tool-Using Agent Environments

arXiv:2609.37315v1 Announce Type: cross Abstract: Tool-using agents are entering settings where a wrong action carries real cost, and the benchmarks certifying them grade what each simulated tool call

Does the Unsafe Gradient Survive a Conversation? On the Fragility of Gradient-Based Jailbreak Detection in Multi-Turn Dialogue

arXiv:2609.36849v1 Announce Type: cross Abstract: Safety-aligned language models are commonly deployed as multi-turn assistants, which lets adversaries spread unsafe intent across several user turns i

FLOORA: A Human-Aligned Domain-Specific Language Model for Architectural Design

arXiv:2609.36064v1 Announce Type: cross Abstract: Foundation models are powerful generators, but many engineering domains require structured representations that general-purpose systems handle poorly.

safetyarxiv-cs-ai

Frontier Autolab: Organizational Memory, Adversarial Dissent and Temporal Leakage in Multi-Agent LLM Firms Across Fifty Years of Technological Change

arXiv:2609.36739v1 Announce Type: cross Abstract: Multi-agent LLM systems are increasingly structured like organizations, with roles, critics and shared memory, yet they are evaluated on tasks that la

Graph-Spectral Flow Matching for Multivariate Time Series Anomaly Detection

arXiv:2609.36765v1 Announce Type: new Abstract: Multivariate time series anomaly detection typically relies on evaluating discrepancies between observations and outputs produced by models trained on n

Local Ai

Guard Models Are Overconfident Where Base Models Are Uncertain

arXiv:2609.36477v1 Announce Type: cross Abstract: Guard models are used as safety classifiers, with confidence scores driving downstream moderation decisions. We evaluate five guard models for prompt

local-aiarxiv-cs-ai

HEIR: Learning Human-Entity Interactions with Functional Roles

arXiv:2609.35955v1 Announce Type: new Abstract: Understanding human-entity interactions requires recovering each person-action event's participants, roles, and shared identities. This structure can su

Hierarchical Utility Calibration for Structured Multiclass Decisions

arXiv:2609.36532v1 Announce Type: cross Abstract: In multiclass probabilistic prediction, Utility Calibration (UC), which focuses auditing on specified utilities, has recently received attention as a

Introducing the CZAR Loss: A Tailored Objective Function for Financial Log-Return Predictions

arXiv:2609.36061v1 Announce Type: new Abstract: In quantitative finance, standard regression losses are misaligned with the economics of return prediction. As the conditional mean of financial log-ret

Tutorials

JudgeProfile: Understanding and Steering Subjectivity in LLM Judges

arXiv:2609.36705v1 Announce Type: new Abstract: LLM judges are inherently subjective, often favoring different responses in pairwise comparison when neither option is objectively wrong. To study this

tutorialsarxiv-cs-ai

Learned Reporting Preferences in RLVR Can Conflict with the Current Request

arXiv:2609.36587v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has become a prominent approach for improving language-model performance on reasoning tasks using

Look What You Made Us Cluster: Hate Narrative Extraction from Reddit Discourse

arXiv:2609.37408v1 Announce Type: new Abstract: Narrative extraction allows us to identify online hate narratives, supporting the construction of rigorous detection systems. Existing computational app

researcharxiv-cs-cl

MMSkillRisk: Can Agents Stay Safe When Multimodal Skills Become Traps?

arXiv:2609.35912v1 Announce Type: cross Abstract: Agent skills are shareable packages of procedural instructions, tools, and examples. Multimodal skills additionally include visual references that age

MotionInsight: Diagnosing Object Motion Deficiencies in Generated Videos

arXiv:2609.37030v1 Announce Type: cross Abstract: Despite rapid progress in video generation models, they still exhibit obvious motion deficiencies, often manifested as incorrect object motion. Howeve

safetyarxiv-cs-ai

OptiCom : A Unified Framework for State-Conditioned Composition in LLM-Driven Optimization

arXiv:2609.37221v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed to solve complex scientific and practical problems via iterative optimization. However, dynamical

Pixels to Keys: Exploring Spatial and Motion Cues in Gameplay Inverse Dynamics

arXiv:2609.37907v1 Announce Type: new Abstract: Video games offer scalable environments for studying perception and control in embodied agents.Abundant online gameplay videos could supply demonstratio

researcharxiv-cs-ai

PowerZooJax: A JAX-based Power System Benchmark for Reinforcement Learning

arXiv:2609.36052v1 Announce Type: new Abstract: Power system operation is a safety-critical sequential decision-making problem, making it a natural testbed for reinforcement learning (RL). However, ex

PrivacySkills: How Privacy Guidance Shapes Source Selection in LLM Agents

arXiv:2609.35937v1 Announce Type: cross Abstract: While prior work has documented privacy failures in LLM agents, it remains unclear how the presentation of privacy guidance influences their choice of

researcharxiv-cs-ai

RAWR: Reward Assignment Without Rollouts in Verifiable Domains

arXiv:2603.17815v2 Announce Type: replace Abstract: Understanding and evaluating multi-step reasoning in LLMs at the level of individual steps remains a key challenge. Process reward models (PRMs) pro

researcharxiv-cs-cl

SelfSearch: Reward-Free Search for Self-Improving Agents

arXiv:2609.37968v1 Announce Type: new Abstract: Advances in the coding capabilities of LLM agents allow them to inspect and modify their own instructions, tools, and execution procedures. Existing app

Agents

Text2Sim: Agentic Physics-Based Simulation Generation with Distilled Expertise

arXiv:2609.36593v1 Announce Type: cross Abstract: Creating diverse physical simulations remains labor-intensive because assets, layout, physical parameters, motion, control, and rendering must be desi

agentsarxiv-cs-ai

UnlearningSoup: Is Repeated Tuning Necessary for Large Language Model Unlearning?

arXiv:2609.37076v1 Announce Type: new Abstract: Large language models trained on vast corpora inherently risk memorizing harmful content that may later re-emerge in their outputs. To mitigate this iss

Agents

WEFT: Scaling Tool-Use Post-Training for General-Purpose Agents

arXiv:2609.36887v1 Announce Type: new Abstract: Recent efforts to scale tool-use post-training have largely centered on the synthesis of executable environments, which constitute only one component of

agentsarxiv-cs-ai

Where Root Cause Analysis Fails: A Retrieval-Reranking Decomposition

arXiv:2609.36686v1 Announce Type: new Abstract: Identifying the root cause of an anomaly among hundreds of sensors is critical for preventing safety incidents and costly downtime in complex monitored

Adapting neural operators for mechanics decisions under changing operating conditions

arXiv:2609.33978v1 Announce Type: cross Abstract: Neural operators can accelerate repeated nonlinear mechanics calculations, but their accuracy can deteriorate as operating conditions move beyond the

ANaLOG: Anisotropic Native-Latent Operator Guidance for Solving Inverse Problems

arXiv:2609.31933v1 Announce Type: cross Abstract: Native-latent guidance is a recent paradigm for solving inverse problems with latent diffusion models. It replaces repeated evaluations of the image-s

researcharxiv-cs-cv

ARCH-B: Architectural Representation, Comprehension and Hierarchy Benchmark

arXiv:2609.34047v1 Announce Type: new Abstract: Multimodal models increasingly interpret visual environments, but their ability to recognize the same building across photographs, floor plans, elevatio

ArticulateArena: A Metric for Articulated Kinematics

arXiv:2609.33931v1 Announce Type: cross Abstract: Modern methods reconstruct or generate simulation-ready articulated objects, predicting not only their geometry but also how their parts are connected

Awaken, Then Scale: Tiny Adaptation for MRI Reconstruction

arXiv:2609.31813v1 Announce Type: cross Abstract: Dormant Awakening (DA) specializes a magnetic resonance imaging (MRI) reconstruction model by fitting a small set of zero weights to one labeled slice

researcharxiv-cs-cv

Beyond Fixed Features: Architecture-Dependent Sensitivity to Node Representations under Heterophily

arXiv:2609.33764v1 Announce Type: new Abstract: Graph Neural Networks (GNNs) perform well on homophilic graphs but struggle in heterophilic settings, where connected nodes often carry dissimilar label

Bidirectional Neural Networks for Global Nucleon-Nucleus Optical Model Calculations

arXiv:2512.22500v4 Announce Type: cross Abstract: Modern nuclear data evaluation increasingly requires not only accurate scattering calculations, but also efficient methods for uncertainty quantificat

Black-Box Auditing of Epistemic Reliability in Multi-Agent Debate Distillation

arXiv:2609.32361v1 Announce Type: new Abstract: Debate distillation adapts weaker verifiers using multi-agent debate transcripts to improve their judgement in subsequent debates, but gains on monitore

CarveMix-RC: Addressing Rare-Class Imbalance Through Lesion-Aware Synthetic Augmentation for Brain Metastasis Segmentation

arXiv:2609.35195v1 Announce Type: new Abstract: Accurate segmentation of post-treatment brain metastases is essential for treatment planning, longitudinal disease monitoring, and quantitative assessme

Change the Product, Keep the Parameters: Associative Algebra Layers for Transformers

arXiv:2609.32814v1 Announce Type: new Abstract: Fast matrix multiplication algorithms keep the product fixed and search for a cheaper way to evaluate it. We instead ask whether a Transformer's learned

CLC-YOLO: A Compact Channel-Gated Prototype Network for Real-Time Leakage-Aware Breast Ultrasound Lesion Segmentation

arXiv:2609.31702v1 Announce Type: new Abstract: Reliable breast ultrasound lesion segmentation requires accurate boundaries and evaluation that prevents patients or duplicate images from crossing data

researcharxiv-cs-cv

Correcting the Dropout-LayerNorm Expectation Gap Improves Protein Structure Models

arXiv:2609.32062v1 Announce Type: cross Abstract: Although E[dropout(x)] = x, here we show that E[LayerNorm(dropout(x))] is not equal to LayerNorm(x). Accordingly, the pattern of a Dropout layer follo

Forecasting Intraday USD/CAD Exchange Rate with News-Derived Monetary-Policy Signals

arXiv:2609.32773v1 Announce Type: cross Abstract: Monetary-policy announcements and central-bank communications play a central role in foreign exchange markets, yet their qualitative, unstructured for

G^3-LoRA: Organizing Reward-Weighted Video Data with Gradient-Guided Grouped LoRA

arXiv:2609.35189v1 Announce Type: new Abstract: Post-training foundation video models on heterogeneous reward-weighted data usually assume that all data categories induce compatible updates. This assu

safetyarxiv-cs-cv

Tutorials

Generative Uncertainty as a Self-supervised Signal for Semantic Similarity Learning

arXiv:2609.35341v1 Announce Type: new Abstract: Evaluating semantic similarity between videos is a fundamental challenge in computer vision, essential for tasks ranging from out-of-distribution (OOD)

tutorialsarxiv-cs-cv

Gravity Falls: A Comparative Analysis of Domain-Generation Algorithm (DGA) Detection Methods for Mobile Device Spearphishing

arXiv:2603.03270v2 Announce Type: replace-cross Abstract: Mobile devices are frequent targets of eCrime threat actors through SMS spearphishing (smishing) links that leverage Domain Generation Algorit

Local Ai

HamiFormer: Dual-Expert Diffusion Fields with Affine Symplectic Maps

arXiv:2609.32838v1 Announce Type: new Abstract: Predicting smooth dynamics and collisions requires modeling continuous evolution and abrupt state changes. We introduce HamiFormer, a dual-expert diffus

local-aiarxiv-cs-lg

Local Ai

HGPTrans: Hierarchical Graph-Pooling Transolver for Automotive Aerodynamic Drag Coefficient Prediction

arXiv:2609.31765v1 Announce Type: new Abstract: Accurate and rapid prediction of the aerodynamic drag coefficient (C_D) is essential for vehicle design, particularly during early-stage styling iterati

local-aiarxiv-cs-cv