Search: “evaluation”

Rubrics as Privileged Information for Open-Ended Generation

arXiv:2608.02948v1 Announce Type: cross Abstract: On-policy self-distillation (OPSD), where a single model acts as both student and teacher with different contexts, has shown promise in verifiable dom

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S^3: Improving Agent Safety through Multi-Stage Defense

DGX agent

arXiv:2608.02683v1 Announce Type: cross Abstract: Large Language Model (LLM) agents rely on multi-stage agentic workflows, with stages such as memory, planning, and tool execution, to accomplish compl

model-releasesarxiv-cs-ai

5 Aug 2026

SAMSEM -- A Generic and Scalable Approach for IC Metal Line Segmentation

arXiv:2603.16548v2 Announce Type: replace-cross Abstract: In light of globalized hardware supply chains, the assurance of hardware components has gained significant interest, particularly in cryptogra

applicationsarxiv-cs-cv

Scalable Frequency- and Length-Aware Subdocument Deduplication for Large Language Model Pretraining

arXiv:2608.03089v1 Announce Type: new Abstract: Large-scale pretraining corpora contain substantial duplicate content. Although document-level deduplication is widely used, removing subdocument-level

safetyarxiv-cs-cl

Scaling an Autoregressive Transformer for Single-Cell Generation

arXiv:2608.02961v1 Announce Type: cross Abstract: We study a self-supervised generation task for single-cell gene expression vectors: given a set of vectors from a cell type, we aim to generate additi

Schedule-Informed Temporal Fusion Forecasting of Hourly Airport Security-Checkpoint Throughput

arXiv:2608.02950v1 Announce Type: new Abstract: Checkpoint staffing requires accurate forecasts of when screening demand will occur, yet flight schedules record departure times rather than passenger a

ScoreField: Neural Inverse Scattering with Score-Based Generative Priors

arXiv:2608.02937v1 Announce Type: cross Abstract: Designing an effective electromagnetic inverse-scattering solver requires faithful enforcement of nonlinear full-wave physics together with an express

SeaSlides: Semantic Abstraction Layer for Agentic Slide Generation

arXiv:2608.03298v1 Announce Type: new Abstract: Agentic presentation generation must preserve source content, maintain coherent visual design, render specialized objects, and produce usable artifacts.

Sedentary Behavior Classification for Wearable Sensors with a CNN-BiLSTM Model

arXiv:2608.02946v1 Announce Type: new Abstract: Accurate detection of sedentary behavior is important for studying health risks related to prolonged sitting, but posture-based classification remains c

Semantic Haptic Feedback Enhances Dexterous Robotic Teleoperation

arXiv:2608.02780v1 Announce Type: new Abstract: In robot teleoperation, haptic feedback can be used to help human operators accomplish dexterous manipulation tasks. However, existing haptic feedback m

applicationsarxiv-cs-ro

Sensitivity, Causality, and Repair Dissociate: A Layer-Wise Analysis of Perturbation Robustness and Its Scaling

model-releasesarxiv-cs-cl

arXiv:2608.03842v1 Announce Type: new Abstract: When a language model fails on surface-perturbed input (typos, OCR noise, homophones), 'which layer is responsible' has three natural operationalization

ShielDroid: A Hybrid Approach Integrating Machine and Deep Learning for Android Malware Detection

arXiv:2608.03250v1 Announce Type: cross Abstract: The rapid advancement of modern technology has led to a significant increase in the use of smart devices, such as smartphones and tablets, resulting i

Should We Type or Talk to LLM Agents? A Comprehensive Study of Voice and Keyboard Input Perturbations

arXiv:2608.03970v1 Announce Type: new Abstract: Human input reaches language models by typing or speaking, and each channel leaves a distinct signature: orthographic noise for keyboards; for voice, di

Single Canonical Prompts Underestimate LLM Safety's Surface-Form Sensitivity

arXiv:2608.02665v1 Announce Type: cross Abstract: A benchmark score is a measurement instrument, yet most benchmarks read each item at a single canonical surface form. We ask whether that reading is f

SKILL-KD: Contrastive Skill Distillation for LLM Agents

arXiv:2607.28048v2 Announce Type: replace Abstract: Skill-based prompting has become a practical mechanism for improving large language model (LLM) agents, yet existing skill acquisition methods often

SocietyBench: Forecasting Counterfactual Social-World Evolution

model-releasesarxiv-cs-cl

arXiv:2608.04009v1 Announce Type: new Abstract: Large language models (LLMs), and the agents built on top of them, are now benchmarked heavily on whether they can finish a task -- fix a bug, drive a b

SparSEEty: Extracting Tokens from Sparsity-Exploiting LLM Serving Systems via Deterministic Side Channels

arXiv:2608.02995v1 Announce Type: cross Abstract: Modern large language models (LLMs) exhibit activation sparsity, wherein only a subset of their neurons is activated for given input tokens. Researche

Speculative Correction: Draft-then-Refine Decoding for Diffusion Language Models

arXiv:2608.02625v1 Announce Type: cross Abstract: Diffusion language models (DLMs) can revise tokens bidirectionally, but standard decoding procedures often adapt them to left-to-right generation by p

Speech LLMs in Low-Resource Scenarios: Data Volume Requirements and the Impact of Pretraining on High-Resource Languages

arXiv:2508.05149v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have demonstrated potential in handling spoken inputs for high-resource languages, reaching state-of-the-art perf

States Hidden in Hidden States: Implicit Discrete State Representations Emerge in LLMs' Hidden States

arXiv:2407.11421v2 Announce Type: replace Abstract: Large Language Models (LLMs) exhibit emergent abilities that may reveal aspects of their internal mechanisms. We study one such capability: directly

researcharxiv-cs-cl

Staying on Spec: Real-Time Monitoring under Uncertainty with a Maritime Case Study

arXiv:2608.02811v1 Announce Type: new Abstract: Robotic systems must operate under uncertainty while satisfying complex task and safety specifications. Monitoring such specifications under uncertainty

safetyarxiv-cs-ro

Strong bounds for large-scale Minimum Sum-of-Squares Clustering

arXiv:2502.08397v3 Announce Type: replace-cross Abstract: Clustering is a fundamental technique in data analysis and machine learning, used to group similar data points together. Among various cluster

Stylometric Defenses Against Author Impersonation in Software Repositories

arXiv:2608.02695v1 Announce Type: cross Abstract: Software supply-chain attacks increasingly exploit an identity gap where compromised maintainer accounts authorize malicious changes. This work evalua

applicationsarxiv-cs-lg

SynEnergy: Anomaly Semantic-Guided Diffusion for Synthetic Energy Data Generation

arXiv:2608.03087v1 Announce Type: cross Abstract: Fine-grained energy consumption data are essential for applications such as demand forecasting, demand response planning, and grid reliability assessm

applicationsarxiv-cs-ai

TARL: Transaction-Aware Reliable Ledgers for Executable Memory Management in Long-Term Agents

arXiv:2608.03699v1 Announce Type: new Abstract: Persistent memory helps long-term agents retain knowledge, yet a single update error can repeatedly distort future retrieval and reasoning. Most existin

Task-Oriented Candidate-Latent Feedback for Coarse-to-Fine Sensing in Distributed OFDM-ISAC Networks

arXiv:2608.03319v1 Announce Type: cross Abstract: Future integrated sensing and communication (ISAC) architectures separate the sensing entity (SE) that acquires measurements from the sensing function

Test Time Adaptation Methods for Point Cloud Registration in Laparoscopic Surgery

arXiv:2608.02883v1 Announce Type: new Abstract: 3D point cloud registration in laparoscopic surgery estimates the transformation between an intraoperative organ reconstructed from video and its preope

safetyarxiv-cs-cv

The Eloquence team submission for task 1 of MLC-SLM challenge

arXiv:2507.19308v2 Announce Type: replace-cross Abstract: In this paper, we present our studies and experiments carried out for the task 1 of the Challenge and Workshop on Multilingual Conversational

applicationsarxiv-cs-cl

The Geometric Nature and a Free Proxy for Flow-Matching Uncertainty

arXiv:2607.27933v2 Announce Type: replace Abstract: Flow matching (FM) has become a popular action head paradigm for modern embodied models. However, as a conditional generative model, it does not exp

The Google Bug Hunters Team admitted to me that they cannot fundamentally patch prompt engineering bypasses in Gemini

Hello everyone Yesterday I gave a report on Gemini bugs and the techniques I learned on Gemini so far with the Engineering Prompt and interestingly today I got a very interesting and controversial ans

model-releasesr-chatgpt

The Tell-Tale Trace: Detecting Reasoning Failures in LLMs Using Chain-of-Thought Dynamics

arXiv:2608.03291v1 Announce Type: cross Abstract: Chain-of-thought (CoT) reasoning improves large language model (LLM) performance while also providing an observable interface to the model's reasoning

TimeRLM: Recursive Language Models Enable Precise Anomaly Localization in Long-Context Time-Series

arXiv:2608.03391v1 Announce Type: new Abstract: Precise anomaly localization over long-context time series is a crucial task in monitoring applications across clinical care, industrial operations, fin

Towards Improving Sequential Decision-Making in LLM Agents via Experience Memory

arXiv:2608.03420v1 Announce Type: new Abstract: Large language models have improved substantially on single-shot reasoning tasks, but their performance in sequential decision-making is less well under

agentsarxiv-cs-ai

UHP Detection: LVLMs have their Unique Hallucination Pattern in the Consistency Space

arXiv:2608.03817v1 Announce Type: cross Abstract: Large vision--language models (LVLMs) demonstrate strong multimodal reasoning capabilities but remain prone to hallucination, where model predictions

Verified Tool Calls Improve LLM Agent Reliability Under Non-Atomic Failures

arXiv:2608.02645v1 Announce Type: cross Abstract: Large Language Model (LLM) agents rely on external tools to perform multistage tasks. Existing agent frameworks typically assume that tool calls are a

agentsarxiv-cs-ai

VIBE: Vector Index Benchmark for Embeddings

arXiv:2505.17810v2 Announce Type: replace Abstract: Approximate nearest neighbor (ANN) search is a performance-critical component of many machine learning pipelines, and rigorous benchmarking is essen

Video-DeepResearch: Towards the Next-Generation Multimodal Deepresearch Agent

arXiv:2608.03979v1 Announce Type: cross Abstract: We introduce Video-DeepResearch (Video-DR), extending multimodal agents from static images to continuous video streams, a setting that demands dense s

Virtual Patients, Real Gains: Digital Twin-Based Simulated CT for Multitask Lung Nodule Analysis

arXiv:2502.21187v4 Announce Type: replace Abstract: AI-based lung cancer screening is constrained by scarce, annotated CT data, particularly for rare nodule presentations. We investigate whether physi

VLC Fusion: Vision-Language Conditioned Sensor Fusion for Robust Object Detection

arXiv:2505.12715v2 Announce Type: replace Abstract: Although fusing multiple sensor modalities can enhance object detection performance, existing fusion approaches often overlook subtle variations in

agentsarxiv-cs-cv

What Language Does and What the Evidence Supports: A Functional Role Taxonomy and Evidence Audit of Language Grounding in Embodied Agents

arXiv:2608.03099v1 Announce Type: new Abstract: Foundation models place language throughout embodied agents, but its presence does not show what it contributes or how well that contribution is grounde

researcharxiv-cs-cl

When Attention Goes Blind: Numerical Failure in ALiBi Positional Encodings

model-releasesarxiv-cs-cl

arXiv:2608.03994v1 Announce Type: new Abstract: We identify a previously overlooked failure mode of ALiBi positional encoding: its linear bias scaling underflows floating-point precision, which zeroes

When Classes Evolve: A Benchmark and Framework for Stage-Aware Class-Incremental Learning

model-releasesarxiv-cs-cv

arXiv:2602.00573v2 Announce Type: replace-cross Abstract: Class-Incremental Learning (CIL) aims to sequentially learn new classes while mitigating catastrophic forgetting of previously learned knowled

When Outputs Disperse, Does Epistemic Revision Follow? A Black-Box Coupling Diagnostic for Machine Collectives

arXiv:2608.03722v1 Announce Type: new Abstract: Collective intelligence research treats disagreement as evidence of epistemic diversity: if agents express different views, the group should retain capa

Where Reasoning Diverges: Localized Multi-Agent Debate for Multi-Hop Question Answering

arXiv:2608.01463v2 Announce Type: replace Abstract: Multi-agent debate commonly exchanges complete rationales even when disagreements concern only a few intermediate claims. We introduce Localized Mul

Wiring Beats Blending: What Transfers Between Transformer Sizes -- and What Doesn't

arXiv:2608.02829v1 Announce Type: new Abstract: Model families train every size from scratch. Can a pretrained large model be converted into a smaller sibling? We characterize the 1.4B->410M conversio

Yes, the AIs were given a cybersecurity challenge, with internet access enabled and safety filters disabled. But the extent to which Mythos …

Yes, the AIs were given a cybersecurity challenge, with internet access enabled and safety filters disabled. But the extent to which Mythos 5 pursued its mission (fake identities, social engineering,

safetyethan-mollick--x

A drone that learns to efficiently find non-uniformly distributed objects in agricultural fields: from simulation to the real world

arXiv:2505.09278v2 Announce Type: replace Abstract: Drones are promising for data collection in precision agriculture but are limited by battery capacity. Drone paths are usually planned using full co

agentsarxiv-cs-ro

4 Aug 2026

A General-Purpose VLM Can Teach an Astronomy Foundation Model to Better Recognize Galaxy Morphology