Search: “evaluation”

BENCHCOMPASS: From Scores to Signals for Training and Harness Decisions in Payment-Domain LLMs

arXiv:2609.18270v1 Announce Type: new Abstract: Payment operations are a critical financial infrastructure, but the value of large language models in this domain remains unclear because payment rules

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Model Releases

Beyond Routine Compliance: Cunning Data Cultivates Safety Vigilance in Large Language Models

DGX agent

arXiv:2609.18515v1 Announce Type: new Abstract: Safety alignment teaches large language models (LLMs) to recognize harmful requests and reject risky instructions. Yet aligned models can fail when harm

model-releasesarxiv-cs-ai

17 Sept 2026

BLADE: ReliaBle Dynamic Hardware-Aware SNN-ANN Boundary SeLection for Event-BAseD Object DEtection

arXiv:2609.17562v1 Announce Type: cross Abstract: Hybrid Spiking Neural Network (SNN)-Artificial Neural Network (ANN) architectures combine the energy efficiency of SNNs with the superior detection ac

local-aiarxiv-cs-ai

Bypassing the Rationale: Causal Auditing of Implicit Reasoning in Language Models

arXiv:2602.03994v3 Announce Type: replace-cross Abstract: Chain-of-thought (CoT) prompting is widely used as a reasoning aid and is often treated as a transparency mechanism. Yet behavioral gains unde

Decoder-Agnostic Token Merging for Vision Transformers: A Systematic Study of G2TM

arXiv:2609.18279v1 Announce Type: new Abstract: Vision Transformers (ViTs) have achieved state-of-the-art performance across a range of computer vision tasks, mainly thanks to the self-attention mecha

Agents

Dependency-Aware Trajectory Refinement for Efficient Multi-Turn Agent Fine-Tuning

arXiv:2609.18417v1 Announce Type: new Abstract: Multi-turn agent trajectories often contain redundant rounds (failed tool calls, parallel sub-queries, verification-only steps) that inflate both traini

agentsarxiv-cs-cl

Disentangling Algorithmic Bias from Archival Artifacts: A Controlled Audit of Vision-Language Model Valuation in Metropolitan Museum Archives

arXiv:2609.17572v1 Announce Type: new Abstract: Auditing vision-language models (VLMs) for societal bias requires distinguishing direct algorithmic valuation disparities from confounders embedded with

local-aiarxiv-cs-lg

English Word Sense Disambiguation in 2026: When the Labels Become the Bottleneck

arXiv:2609.17554v1 Announce Type: new Abstract: In English all-words word sense disambiguation (WSD), the labels, not the models, have become the bottleneck: frontier LLMs are accurate enough that the

Entropy in Conversational AI: Structured Unpredictability as Inferrable Interiority

arXiv:2609.19044v1 Announce Type: new Abstract: Sampling can increase response diversity without producing history-dependent behavior. We formalize a different design target, structured unpredictabili

local-aiarxiv-cs-cl

FairCompressAgent: An Agentic Framework for Fairness-Aware Model Compression for FPGA Deployment

arXiv:2609.17786v1 Announce Type: new Abstract: Fairness-aware model compression requires selecting methods and configurations that balance accuracy, fairness, and deployment cost. These decisions bec

safetyarxiv-cs-ai

Tutorials

Fallacy Benchmarks Measure Scheme Recognition, Not Fallacy Detection

arXiv:2609.18644v1 Announce Type: new Abstract: Fallacy-detection benchmarks pair fallacy classes with a single 'valid' or 'none' class that takes everything data collection did not label as a fallacy

tutorialsarxiv-cs-cl

Applications

ForwardDLO: Model-Based Bimanual Shape Matching of Unconstrained Deformable Linear Objects

arXiv:2609.18455v1 Announce Type: new Abstract: Ropes, cables, and other deformable linear objects appear in tasks from untangling to cable routing and suturing, yet controlling their shape remains a

applicationsarxiv-cs-ro

Hardware-Free Robotics Laboratories in Mixed Reality

arXiv:2609.18434v1 Announce Type: new Abstract: Teaching robotics relies on screen-based simulation, showing robot motion in an abstract coordinate frame rather than at real scale in the learner's own

safetyarxiv-cs-ro

HearInContext: A Benchmark for Implicit Context in Speech Recognition

arXiv:2609.18680v1 Announce Type: new Abstract: Contextual ASR can benefit from semantic cues or from target words explicitly provided in the context. We introduce HearInContext, a Mandarin--English b

Agents

Hypothesis-Driven Autonomous Materials Synthesis with Multimodal LLM Agents

arXiv:2609.18598v1 Announce Type: cross Abstract: Self-driving laboratories can explore synthesis conditions autonomously, but their decision-making layer is typically a black-box optimizer, and the o

agentsarxiv-cs-ai

JigSync: Gauge-Resolved Synchronization for Jigsaw Reassembly under Unknown Piece Orientation

model-releasesarxiv-cs-cv

arXiv:2609.18379v1 Announce Type: new Abstract: Square jigsaw reassembly requires recovering the spatial arrangement of shuffled fragments from their visual content and pairwise relationships. While r

Label-Confidence-Aware Uncertainty Estimation in Natural Language Generation

arXiv:2412.07255v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) demonstrate remarkable capabilities in generative tasks but pose potential risks due to their tendency to generat

safetyarxiv-cs-ai

LangSelect: Cost-Aware Target-Language Routing for LLM Code Generation

arXiv:2609.18959v1 Announce Type: new Abstract: LLM code-generation systems usually choose a target programming language before decoding and treat that choice as fixed. We show that, for language-flex

Long-Lived Characters, Local Inference: Incremental Memory Maintenance for Game NPCs

arXiv:2609.18935v1 Announce Type: new Abstract: A game character should not have to reread its entire life before every conversation. For locally deployed language-model characters, however, revising

Machine Translation between English and Syriac (East Syriac Dialect) using Statistical Machine Learning

arXiv:2609.18529v1 Announce Type: new Abstract: UNESCO considers the Assyrian (Syriac) language an endangered language. Although Assyrians speak the language worldwide, the speaking population is unce

safetyarxiv-cs-cl

MiST: Mid-Training LLMs for Cybersecurity

arXiv:2609.18496v1 Announce Type: cross Abstract: Cybersecurity combines high-stakes analysis with complex technical language, making it an impactful and challenging domain for LLMs. We present MiST (

MSR: Multiple Subject Reference for Video Generation

model-releasesarxiv-cs-cv

arXiv:2609.18393v1 Announce Type: new Abstract: Conditioning a video generator on multiple images requires preserving appearance while associating each reference with its intended role. We present MSR

Not All Patches Are Equally Forgettable: Spatially Localized Domain Unlearning in Vision-Language Models

arXiv:2609.17790v1 Announce Type: new Abstract: Pre-trained vision-language models (VLMs) exhibit strong cross-domain recognition performance even without additional training. However, this robustness

Objective vs. Search: Decomposing What Makes a Good Tokeniser

arXiv:2609.19145v1 Announce Type: cross Abstract: Two dominant tokenisation algorithms are used by modern language models: byte-pair encoding (BPE) and UnigramLM. These differ along two orthogonal axe

researcharxiv-cs-ai

Online Multimodal Workload Assessment in Contact-Rich Physical Human-Robot Interaction

arXiv:2609.18031v1 Announce Type: new Abstract: Contact-rich physical human--robot interaction (pHRI) imposes time-varying demands associated with physical interaction, motor regulation, and physiolog

researcharxiv-cs-ro

PACT: Can Enterprise AI Assistants Be Trusted Under Pressure?

arXiv:2609.18605v1 Announce Type: cross Abstract: As corporate AI adoption continues to grow, enterprise-grade LLM agents are being deployed into sensitive contexts such as hiring, healthcare, and fin

PANORAMA: Panoptic Grounded Captioning via Mask Proposal Selection

arXiv:2609.19143v1 Announce Type: cross Abstract: Intelligent systems that act in the world require image understanding that is both comprehensive and spatially grounded. Current vision-language model

Peak-Aware Short-Term Load Forecasting Across Distribution Grid Aggregation Levels

arXiv:2609.18588v1 Announce Type: new Abstract: For distribution system operators, short-term load forecasting (STLF) supports congestion management, voltage control, and asset protection. Most existi

PersonaPath: Towards Knowledge-Centric Personalized Learning Path Planning

arXiv:2609.18861v1 Announce Type: new Abstract: Adaptive learning systems commonly formulate learning path planning as Exercise-Centric (EC) recommendation, where the next step is inferred from item-l

Physics-based prediction, uncertainty quantification and decision-making for IN718 crystallographic texture intensity across LPBF defocus regimes

arXiv:2609.18863v1 Announce Type: new Abstract: Reliable prediction of crystallographic texture in laser powder bed fusion is critical for linking process conditions with anisotropic response and for

Q-BIOLAT: Binary Latent Protein Fitness Landscapes for QUBO-Based Optimization

arXiv:2603.27526v2 Announce Type: replace Abstract: Protein fitness optimization is a discrete search problem, and the representation used for prediction also determines the neighborhood graph travers

RAFAIL: Relationship-Aware Failure Detection for Robotic Manipulation

arXiv:2609.18324v1 Announce Type: new Abstract: Detecting failures during execution is essential for reliable robotic manipulation. Vision-language models (VLMs) can assess task outcomes semantically

safetyarxiv-cs-ro

ReDIL-GNN: Resynthesis Domain Incremental Learning for Circuit Graph Neural Networks

arXiv:2609.18595v1 Announce Type: new Abstract: Logic resynthesis preserves circuit functionality while changing gate vocabulary, topology, and structural statistics, creating domain shift for circuit

ReRadar: Robust Radar Global Localization via Rotation-Equivariant Descriptor Learning

arXiv:2609.18092v1 Announce Type: new Abstract: Global localization with scanning millimeter-wave radar remains challenging because place-recognition descriptors often discard spatial structure needed

local-aiarxiv-cs-ro

Rethinking Domain Specialization for Open-Ended Scientific Reasoning in Astronomy Language Models

arXiv:2609.17644v1 Announce Type: cross Abstract: Domain-specialized language models are widely used for scientific question answering, but stronger general-purpose systems raise a sharper question: w

Securing quantum error correction against misleading advice from AI agents

arXiv:2609.19090v1 Announce Type: cross Abstract: Can an attacker turn influence over an artificial intelligence (AI) adviser into a harmful quantum error-correction update? We identify an ambiguity i

researcharxiv-cs-ai

Selection Is Retrieval, Abstention Is Not: On-Device Tool Routing over 70 Korean-English Actions

arXiv:2609.18672v1 Announce Type: new Abstract: An AI assistant that calls tools makes two decisions on every request: which tool to invoke, and whether any available tool applies. In the usual design

local-aiarxiv-cs-cl

STRADAViT: Self-Supervised Domain Adaptation of Vision Transformer Backbones for Radio Astronomy

arXiv:2603.29660v4 Announce Type: replace-cross Abstract: Next-generation radio astronomy surveys are delivering millions of resolved sources, yet scalable morphology analysis remains difficult across

Hardware

The Inference Engineering Pareto Atlas: Which Optimizations Dominate the Cost, Quality, and Latency Frontier?

arXiv:2609.17863v1 Announce Type: new Abstract: LLM inference optimizations report speedups on different models, GPUs, prompts, and quality metrics, making them hard to compare or combine. We build a

hardwarearxiv-cs-ai

The Mirage of Calibrated Confidence: Trajectory-Independence of Verbalized Confidence in Vision-Language Models

arXiv:2609.18453v1 Announce Type: new Abstract: A calibrated Vision-Language Model (VLM) can repeatedly self-correct, say 'Wait, I should recheck,' arrive at the wrong answer, and still report high co

researcharxiv-cs-ai

The Missing 'I Don't Know': Why Three Reasoning-Reliability Findings Converge on Calibrated Abstention

arXiv:2609.17686v1 Announce Type: cross Abstract: Three recent results describe what look like unrelated LLM reliability problems. Yin et al. (2026) show reasoning RL collapses tool-reliability repres

The Unbearable Weight: Scaling Models and Methods for UAV Audio Classification

model-releasesarxiv-cs-lg

arXiv:2609.17884v1 Announce Type: cross Abstract: As unmanned aerial vehicles (UAVs) become increasingly prevalent in consumer and defense settings, classifying them reliably from limited, modality-sp

TRACER: Adaptive Multi-Robot Social Navigation via Joint Human-Response Prediction and Interaction-Aware Replanning

model-releasesarxiv-cs-ro

arXiv:2609.18776v1 Announce Type: new Abstract: Multi-robot navigation in human-shared spaces is inherently interactive: coordinated robot motions influence how nearby entities respond, while those re

Understanding Dynamic Scenes at Gigapixel Scale: Wide-Area Spatio-Temporal Perception from UAVs

arXiv:2609.18210v1 Announce Type: new Abstract: UAV-borne imaging has advanced from megapixel to gigapixel sensors, shifting aerial perception from recognizing individual targets to understanding enti

Tutorials

Variational Quantum Transformer Architecture for Synthetic Language Generation

arXiv:2609.18565v1 Announce Type: cross Abstract: We propose a compact NISQ-compatible quantum transformer architecture for synthetic QNLP sequence modelling. The model preserves the autoregressive ne

tutorialsarxiv-cs-cl

VCTP: Vehicle-Conditioned Terrain Planning for Off-Road Navigation

arXiv:2609.17834v1 Announce Type: new Abstract: A vehicle's heading affects both the surfaces beneath its tires and its pitch and roll. We present Vehicle-Conditioned Terrain Planning (VCTP), which re

researcharxiv-cs-ro

Voice of Reason: Reinforcement Learning for Spoken Math

arXiv:2609.18677v1 Announce Type: new Abstract: Speech language models enable richer spoken interactions between humans and machines than cascaded systems, allowing access to paralinguistic informatio

researcharxiv-cs-cl

VoiceTrace: A Benchmark and Retrieval Framework for Who-Said-What Speech Retrieval

arXiv:2609.18521v1 Announce Type: cross Abstract: Speech retrieval has become increasingly important as spoken content continues to grow across meetings, lectures, podcasts, and videos. Existing bench