Search: “evaluation”

Alignment Faking - the Train -> Deploy Asymmetry: Through a Game-Theoretic Lens with Bayesian-Stackelberg Equilibria

arXiv:2511.17937v2 Announce Type: replace Abstract: Alignment faking is a form of strategic deception in AI in which models selectively comply with training objectives when they infer that they are in

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An Initial Study of Physiological Markers for Deepfake Speech Detection

DGX agent

arXiv:2610.18934v1 Announce Type: cross Abstract: Conventional deepfake speech detectors primarily target synthesis artifacts and often degrade under unseen attacks or recording conditions. Human spee

applicationsarxiv-cs-cv

15 Oct 2026

Analyzing the Dynamics of WSBM-based Echo State Networks using InputDSA

arXiv:2610.15380v1 Announce Type: new Abstract: Bridging the structural gap between biological brains and artificial neural networks presents a pathway to altered computational dynamics. This paper in

Agents

ANASSA: From High-Level Framework to Low-Level Architecture for Spatial Agentic AI

arXiv:2610.14382v1 Announce Type: new Abstract: Agentic AI systems operating over geospatial data require more than autonomous reasoning and tool use; they must also support explicit orchestration, sp

agentsarxiv-cs-ai

Anuvani-Diarization: Zero Shot Speaker Diarization and Annotation Conventions Across 22 Languages

arXiv:2610.20327v1 Announce Type: new Abstract: India's 22 scheduled languages are spoken by over a billion people in conversations that mix languages, often within one turn, overlap freely, and take

Atomic-WAM: Execution-Grounded Atomic-Motion Reasoning for World Action Models

arXiv:2610.20157v1 Announce Type: new Abstract: World Action Models (WAMs) typically adapt video foundation models to robotic control through joint video and action prediction. However, task-level ins

researcharxiv-cs-ro

Back on Track: Deployment-time Policy Improvement via World Model Planning

arXiv:2610.19579v1 Announce Type: new Abstract: State-of-the-art visuomotor policies are increasingly capable of executing complex tasks, yet can fail during deployment in ways they cannot predict or

safetyarxiv-cs-ro

Benchmarking 3D Reconstruction for Under-Ice Robotic Perception in Arctic Environments

model-releasesarxiv-cs-ro

arXiv:2610.19097v1 Announce Type: new Abstract: As the Arctic transitions toward a seasonally ice-free state, capturing the complex morphology of submerged sea ice is crucial for advancing models of o

Benchmarking Quantum Kernel SVMs for Credit Card Fraud Detection: Performance Realities Under NISQ Constraints

arXiv:2610.17027v1 Announce Type: new Abstract: Detecting credit card fraud is notoriously difficult because fraudulent charges make up less than 0.2% of total transactions. Quantum Machine Learning (

Beyond Aggregate Accuracy: Item-Level Transitions in Prompt Optimization

arXiv:2610.19084v1 Announce Type: cross Abstract: Automatic prompt optimization (APO) uses feedback from model responses to improve prompts automatically. However, its effectiveness is usually measure

Beyond Answer Voting: Fine-Grained Correction of LLM Reasoning through Graph Alignment across Sampled Traces

arXiv:2610.18606v1 Announce Type: new Abstract: Large language models increasingly tackle tasks that require multi-step reasoning, where errors in intermediate claims can affect the final answer. Self

Beyond Black Boxes: Visual Grounding for Text Embeddings

arXiv:2610.18047v1 Announce Type: new Abstract: In this paper, our goal is to represent text embeddings as sketches for three main reasons. First, to visualize text representation and to explore their

Beyond Corrected Actions: Training LLM Agents on Textual Critiques

arXiv:2610.19367v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for multi-turn agentic tasks that require interactions with users and environments over extended sequ

Beyond Equation Search: Conjecture-Guided Discovery with SCOPE and ClosureBench

model-releasesarxiv-cs-lg

arXiv:2610.18938v1 Announce Type: cross Abstract: Most symbolic regression methods optimize candidate equations, but improving an equation's fit does not establish whether its underlying scientific co

Beyond Expert Rankings: Contrast Calibration for Mixed-Precision MoE Quantization

arXiv:2610.20353v1 Announce Type: new Abstract: Mixture-of-experts (MoE) language models activate only a few experts per token, yet all expert weights must be stored. Mixed-precision quantization redu

researcharxiv-cs-lg

Beyond Outcome Feedback: Trajectory-Quality-Guided Experience-based Learning

arXiv:2610.14877v1 Announce Type: new Abstract: Experience-based learning enables large language model (LLM) agents to improve over time by reusing knowledge from past executions. However, existing me

Beyond Perfect Teammates: Multi-Agent Collaboration with Unreliable Colleagues

arXiv:2610.16117v2 Announce Type: new Abstract: LLM-based multi-agent collaboration is increasingly used to solve complex tasks by dividing work among specialized agents and integrating complementary

Beyond Size: How Gradients Shape Pruning Decisions in Large Language Models

arXiv:2311.04902v3 Announce Type: replace Abstract: Large Language Models (LLMs) with billions of parameters are prime targets for network pruning, which removes some model weights without hurting per

Beyond Static Cues: Unified Dynamic Detection of MLLM Backdoors via Dual-Flow Trajectory Analysis

arXiv:2610.20319v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) are increasingly deployed in safety-critical domains, yet their susceptibility to backdoor attacks remains a fo

safetyarxiv-cs-cv

Agents

Beyond the Verdict: Agentic Code Judging with Verifiable Feedback

arXiv:2610.18760v1 Announce Type: new Abstract: Test-time scaling for large language models (LLMs) can involve generating multiple candidate solutions for selection or revising an earlier attempt. To

agentsarxiv-cs-ai

bharatSetu: a 1M x 22 bridge for indic translation

arXiv:2610.15705v1 Announce Type: cross Abstract: India's Eighth Schedule recognises 22 languages, yet parallel data is uneven across them, and many language pairs, especially among lower-resource lan

Boosting the Learning for Ranking Patterns

arXiv:2610.16511v1 Announce Type: new Abstract: Pattern mining is a valuable tool for exploratory data analysis, but identifying relevant patterns for a specific user is challenging. Various interesti

Calibrated Typed Decisions for Entity, Relation, and Event Extraction

arXiv:2610.17113v1 Announce Type: cross Abstract: Information extraction models often perform well on the datasets they are trained on, but transferring to new domains and annotation guidelines remain

Can Agents Truly Forget? Explore Machine Unlearning for LLM Agents

arXiv:2610.17659v1 Announce Type: new Abstract: Large language model (LLM) agents have shown strong capabilities in interactive problem solving, tool use, and long-horizon task execution. However, the

Can LLM Agents Efficiently Identify Appliance Faults? Insights From Diagnosing a Simulated Appliance

arXiv:2610.19291v1 Announce Type: new Abstract: In so-called 'Industry 4.0,' integrated sensors, analytics tools, and other digital technologies supplement industrial workflows, potentiating enhanced

CARD: Closing the Teacher-Student Loop for Adversarial Robustness Distillation

arXiv:2610.19911v1 Announce Type: cross Abstract: Adversarial robustness distillation typically treats a robust teacher as a fixed knowledge source and transfers robustness to a compact student in a o

researcharxiv-cs-cv

Cascaded Retrieval with Cross-Modal Query Refinement for Efficient Visual Document Search

arXiv:2610.20367v1 Announce Type: new Abstract: Retrieving information from visually rich documents requires matching queries against pages that contain complex evidence in tables, figures, and layout

researcharxiv-cs-cl

Certifying Almost-Sure Reachability in Unknown MDPs

arXiv:2610.18119v1 Announce Type: cross Abstract: {em Specification-Guided Reinforcement Learning (RL)} has largely concerned itself with learning an optimal policy against a formal specification in a

Chain Dimension Scaling: Communication-Efficient Loop-Style Scaling for Industrial Short-Video Ranking

arXiv:2610.16415v1 Announce Type: new Abstract: Industrial recommendation rankers keep scaling in width and depth to billions of parameters, but this increasingly incurs costs in parameter growth, dis

Applications

Chain of Time: In-Context Physical Simulation with Image Generation Models

arXiv:2511.00110v2 Announce Type: replace Abstract: We propose a novel cognitively-inspired prompting method to stabilize and interpret the physical simulation produced by autoregressive image generat

applicationsarxiv-cs-cv

Agents

ClawLoop: Self-Improving Agents via Harness-Native Training Loop

arXiv:2610.14118v1 Announce Type: new Abstract: The rapid advancement of Large Language Models (LLMs) has driven their deployment toward general-purpose harness environments, where LLM-based agents op

agentsarxiv-cs-ai

CLIVO: Differentiable Cluster-Based Instruction Mixing with Learned Validation Objectives

arXiv:2610.16876v1 Announce Type: new Abstract: Target-aware multimodal instruction selection requires useful examples and an appropriate balance of supervision. Sample-level rankings can overrepresen

CockpitHAT: Dependency-Graph-Driven Hierarchical Attribution for Embodied Multi-Agent Cockpits

arXiv:2608.01805v2 Announce Type: replace Abstract: LLM multi-agent systems suffer from Correctness Collapse, where high task-level accuracy conceals severe process-level failures. This is especially

Collective Learning for Unified Robotic Manipulation via Predictive Dynamics Adaptation

arXiv:2610.19141v1 Announce Type: new Abstract: Learning a collective policy for state-based Cartesian manipulation across diverse robotic embodiments presents a fundamental challenge due to embodimen

safetyarxiv-cs-ro

CommerceGen-Studio: An End-to-End Framework for Commercial-Grade Main-Image Generation

model-releasesarxiv-cs-cv

arXiv:2610.20603v1 Announce Type: new Abstract: We present CommerceGen-Studio, an end-to-end framework for generating commercial-grade main images for e-commerce Stock Keeping Units (SKUs). Our framew

Compare to Correct: Pairwise-Guided Logit Adjustment for LLM Test-Time Scaling

arXiv:2610.18583v1 Announce Type: new Abstract: Sampling-based test-time scaling enhances LLM reasoning by aggregating multiple reasoning paths for the same query. Existing methods use answer frequenc

CondMSP: Condition-Informed and Resource-Aware Inorganic Materials Synthesis Planning

arXiv:2610.15603v1 Announce Type: new Abstract: Materials synthesis planning (MSP) connects AI-driven materials discovery to experimental realization by proposing precursors, synthesis operations, and

Confidently Wrong: Detecting Hallucinations in Financial Question Answering from LLM Internal States

arXiv:2607.11414v2 Announce Type: replace Abstract: Large language models (LLMs) in financial applications fail most consequentially when they are confidently wrong. Hedged, uncertain answers invite s

Constitutive parameterized deep energy method for solid mechanics problems with random material parameters

model-releasesarxiv-cs-lg

arXiv:2603.26030v2 Announce Type: replace Abstract: In practical structural design and solid mechanics simulations, material properties inherently exhibit random variations within bounded intervals. H

Continual Learning for Reliable In-Sequence Molecular Communication

arXiv:2610.20426v1 Announce Type: new Abstract: This paper considers reliable in-sequence molecular communication, where bio-nanomachines exchange molecule-encoded information in a specified order, an

researcharxiv-cs-lg

Continual pretraining Prostate MRI ViT Encoder for task alignment

arXiv:2610.20217v1 Announce Type: new Abstract: Building foundation models for MRI has emerged as a promising direction for advancing medical image analysis and improving accessibility of task specifi

safetyarxiv-cs-cv

Contrastive uncertainty learning for robust multi-structure segmentation in lower-pelvic MR

arXiv:2610.20251v1 Announce Type: new Abstract: Boundary delineation of anatomical structures in prostate MRI is often compromised by regional ambiguity. Automated segmentation methods relying on glob

safetyarxiv-cs-cv

Convex-Analytic View of Query Selection for Safety Verification of Markov Decision Processes

arXiv:2610.17541v1 Announce Type: cross Abstract: Safety verification of a Markov decision process (MDP) asks whether the probabilities of reaching several failure states jointly lie in a convex safe

Correct Choices, Failed Sequences: Choice2Seq Benchmarks Correctness Retention Across Output Interfaces

arXiv:2610.16191v1 Announce Type: new Abstract: A model may select the correct answer yet fail to construct it through a sequence of local decisions. We introduce Choice2Seq, a diagnostic benchmark th

Correction Training for Diffusion Models

arXiv:2610.14136v2 Announce Type: new Abstract: Iterative sampling in diffusion models can lead to error accumulation due to exposure bias. The denoiser is trained on real images interpolated with noi

Correlation-Aware Contextual Bandits with Surrogate Rewards for LLM Routing

arXiv:2607.09015v2 Announce Type: replace Abstract: We study contextual bandit problems with correlated arms and access to surrogate reward signals produced by a machine learning model, motivated by a

researcharxiv-cs-lg

Cortex: Consolidating Context into Parametric Memory

arXiv:2610.20399v1 Announce Type: new Abstract: Context can improve large language model performance, but these gains may be lost after context removal. Inspired by biological systems consolidation, w

researcharxiv-cs-cl

Cowork-Gym: Synthesizing Interactive Work Environments at Scale

arXiv:2610.17670v1 Announce Type: new Abstract: Cowork agents navigate dependencies across tools and files while adapting to changing user requirements and edits to shared workspaces. Scaling such env