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Likelihood Ranking doesn't Scale Like Prompting in LLMs

arXiv:2609.29390v1 Announce Type: new Abstract: LLM evaluation is commonly performed either by prompting models to produce answers or by scoring candidate outputs with likelihood-based metrics. In mul

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LLM Forensics: Where Do Backdoors Hide? Localizing and Controlling Trigger Mechanisms with Sparse Autoencoders

DGX agent

arXiv:2609.07746v2 Announce Type: replace Abstract: Even though backdoors in LLMs have been a growing concern, their inner workings are still under heavy scrutiny. Trigger-based backdoors are easy to

researcharxiv-cs-cl

25 Sept 2026

LLM surprisal is necessary but not sufficient to capture English garden-path effects: Evidence from joint latent modeling of reading paradigms

arXiv:2602.04489v2 Announce Type: replace Abstract: Temporarily ambiguous garden-path sentences ('While the team trained the striker wondered... ') are known to cause processing difficulty, which can

Machine Unlearning for Gibbs Supervised Learning Algorithms

arXiv:2609.29409v1 Announce Type: cross Abstract: In this paper, a method for achieving exact unlearning for Gibbs supervised learning algorithms is proposed using a variational formulation inspired b

Matrix Aggregation Operators

arXiv:2609.28562v1 Announce Type: cross Abstract: Aggregation theory has traditionally focused on operators defined over vectors. However, many applications-including Multi-Criteria Decision Making, G

MDE-VIO: Enhancing Visual-Inertial Odometry Using Learned Depth Priors

arXiv:2602.11323v2 Announce Type: replace Abstract: Traditional monocular Visual-Inertial Odometry (VIO) systems struggle in low-texture environments where sparse visual features are insufficient for

Med-AR: Autoregressive Vision-Language Pretraining for Long-Tailed Chest X-Ray Classification and Uncertainty-Aware Evaluation

arXiv:2609.29156v1 Announce Type: cross Abstract: Long-tailed chest X-ray classification requires visual representations that capture both common abnormalities and subtle, infrequent findings. We prop

MemGuard-Alpha: Limits of Membership Inference for Detecting and Filtering Memorization-Contaminated Signals in LLM-Based Financial Forecasting

arXiv:2603.26797v2 Announce Type: replace Abstract: Large language models are increasingly used to generate financial alpha signals, but many have memorized the historical data in their training corpo

Mind the Gap: Mesh-Guided Repair of Broken Vessels

arXiv:2609.29779v1 Announce Type: new Abstract: Vessel segmentation is commonly optimized as voxel-wise classification, but small local errors can strongly disrupt vascular connectivity while having l

Modeling Load-, Velocity-, and Temperature-Dependent Transmission Errors of Cycloidal Drives for Industrial Robots Using Fourier Series

arXiv:2609.29112v1 Announce Type: new Abstract: Industrial robots are rarely used for machining tasks due to their limited path accuracy. This accuracy is mainly limited by inaccuracies in the drive t

researcharxiv-cs-ro

Modelling dynamic systems transfer functions from events in computational neuromorphic imaging

arXiv:2609.29863v1 Announce Type: new Abstract: Event Vision Sensing (EVS) report threshold crossings of log-irradiance, so a static optical system imaging a static scene produces no output at all. Th

Monitoring Urban Traffic Dynamics at Fine Spatiotemporal Resolution Using Distributed Acoustic Sensing and Deep Learning

arXiv:2609.28793v1 Announce Type: new Abstract: Mapping the distribution of traffic dynamics at high spatiotemporal resolution is a fundamental question in transportation research. Distributed acousti

MORE-PLR: multi-output regression employed for partial label ranking

arXiv:2609.29386v1 Announce Type: new Abstract: The partial label ranking problem is a supervised learning scenario that aims to fit a preference model that predicts a bucket order defined over a set

MoSign: Challenge-Response Motion-Watermark Authentication for Anonymous Virtual-Reality Users

arXiv:2609.29603v1 Announce Type: cross Abstract: Social virtual reality (VR) creates a paradox. A user's body motion is a high-entropy biometric: head and hand trajectories alone re-identify users am

MQSS-Selector: RL-Guided Pass Selection for an MLIR Compilation Pipeline

arXiv:2609.30104v1 Announce Type: cross Abstract: High Performance Computing (HPC) and Quantum Computing (QC) systems are increasingly converging towards unified High Performance Computing-Quantum Com

Multi-Task Learning by using Contextualized Word Representations for Syntactic Parsing of a Morphologically Rich Language

arXiv:2609.29855v1 Announce Type: cross Abstract: We address the challenge of syntactic parsing for Urdu, a morphologically rich language, and present state-of-the-art results for both constituency an

Named Entity Recognition using Sliding Window Approach

arXiv:2609.29682v1 Announce Type: new Abstract: Named Entity Recognition (NER) is a core NLP task, but transformer-based sentence-level models struggle with long documents because of fixed input-lengt

No More Free Lunch: Corpus Task Complexity Matters as Corpora Grow

arXiv:2609.29245v1 Announce Type: cross Abstract: Given a large corpus, the questions one might ask can vary -- from 'When was the first human heart transplant?' to 'What are all the contradictory cla

Nuclear Norm-Regularized Bayesian Matrix Completion

arXiv:2609.30078v1 Announce Type: cross Abstract: Matrix completion, the problem of estimating missing entries in a matrix from noisily observed ones, underlies a diverse array of problems such as rec

OceanXL: Large-scale Underwater 3D Gaussian Splatting via Block Partitioning and Adaptive Pruning

arXiv:2609.29985v1 Announce Type: new Abstract: Underwater 3D reconstruction is critical for marine exploration, ecological monitoring, and subsea infrastructure inspection, yet remains challenging at

On Growth and Form, and Function: Reusable Regulatory Handles Control Phenotypic Variation

arXiv:2609.29755v1 Announce Type: cross Abstract: How phenotypic transformations are implemented by changes in underlying regulatory dynamics remains a central question in developmental biology. Inspi

On the second-order optimization for spiking neural networks

arXiv:2609.29379v1 Announce Type: cross Abstract: Spiking Neural Networks (SNNs) offer an energy-efficient alternative to conventional neural networks by exploiting sparse, binary spikes, and event-dr

On the SoS Certifiability of Log-Concave Distributions

arXiv:2609.30105v1 Announce Type: new Abstract: For an arbitrary isotropic log-concave distribution P on R^d, we prove that the polynomial (Cm)^m|v|_2^m - E_{Xsim P}langle X,vrangle^m is a sum of squa

OncoVision: Integrating Mammography and Clinical Data through Attention-Driven Multimodal AI for Enhanced Breast Cancer Diagnosis

arXiv:2511.19667v2 Announce Type: replace Abstract: OncoVision is a privileged-information training framework that uses mammography images and clinical features during training and performs inference

Only What Was Seen: Observation-Gram Compaction of View-Dependent Appearance in 3D Gaussian Splatting

arXiv:2609.28997v1 Announce Type: new Abstract: Most of the memory of a 3D Gaussian Splatting model holds spherical-harmonic colour coefficients, yet each Gaussian is seen only from the narrow cone of

Ontology-Mediated Neurosymbolic Constraint Acquisition from Multiple Stakeholders

arXiv:2609.29876v1 Announce Type: new Abstract: Neurosymbolic research typically assumes a pre-existing symbolic specification, leaving the upstream challenge of acquiring and formalizing requirements

Parts-of-Speech as Emergent Categories in SAE Latent Space

arXiv:2609.29362v1 Announce Type: new Abstract: Sparse AutoEncoders (SAEs) offer a promising way to inspect language model representations, but it is still unclear what kind of linguistic structure th

Path-specific harm decomposition: A partial identification framework

arXiv:2609.29938v1 Announce Type: cross Abstract: A central goal when designing treatment policies is often to 'do no harm', that is, to avoid interventions that improve average outcomes while worseni

PEEL: Physics-Enabled Evidential Learning for Identifiable Uncertainty in CT Imaging

arXiv:2609.29599v1 Announce Type: new Abstract: Normal-inverse-gamma (NIG) regression is not uniquely identifiable from its marginal Student-t likelihood: the likelihood determines three combinations

Physics and Data Driven Transformer-Mamba Framework for Flow Field

arXiv:2609.29087v1 Announce Type: new Abstract: While deep learning accelerates expensive partial differential equation solving in computational fluid dynamics (CFD), existing methods like PINNs and F

Physics-Guided Multi-Objective Deep Learning for Ultrasound RF Data Interpolation in Resource-Constrained Imaging

arXiv:2609.28775v1 Announce Type: cross Abstract: Ultrasound imaging increasingly targets portable, point-of-care, and wearable settings where constraints on power, bandwidth, and hardware complexity

Pose Adaptive Dynamic FiLM Modulation for Visual Speech Recognition

arXiv:2609.29443v1 Announce Type: new Abstract: Head-pose variation introduces substantial appearance transformations in visual speech recognition (VSR), making pose-aware feature modulation desirable

Post-Training Leaves Behavioral Shadows on Unrelated Decisions

arXiv:2609.29233v1 Announce Type: cross Abstract: We find that language models can transfer capabilities through task-unrelated text. Post-training typically improves language models using task-specif

Predicting Emerging Topics from Outliers: A Prospective Study of Weak Signals in Embedding Space

arXiv:2609.29183v1 Announce Type: new Abstract: Some documents that embedding-based topic models initially classify as noise later become founding members of emerging topics. At publication time, howe

PROVE: Proof-guided Regime-aware Operator Verification for Hallucination Detection in Medical Visual Question Answering

arXiv:2609.29604v1 Announce Type: new Abstract: In medical visual question answering (VQA), hallucinations of vision-language models (VLMs) may lead to confident but incorrect responses, raising the r

pylazaro: a Python package for anglicism extraction in Spanish

arXiv:2609.29276v1 Announce Type: new Abstract: Lexical borrowings are words from one language that are introduced into another language. Identifying lexical borrowings in text is a relevant task for

Quantum Attention by Overlap Interference: Predicting Classical and Many-Body Quantum Sequences

arXiv:2602.06699v2 Announce Type: replace-cross Abstract: We propose a variational quantum implementation of self-attention (QSA)-the core operation in transformers and large language models-which pre

RD-JEPA: Predictive latent pretraining for few-trajectory transfer across reaction--diffusion equations

arXiv:2609.29403v1 Announce Type: new Abstract: Learning surrogates for time-dependent partial differential equations often requires a new simulation corpus when the governing operator changes. We int

Reachability-Based Formal Verification of Graph Neural Networks with Node and Edge Features

arXiv:2609.30079v1 Announce Type: cross Abstract: Graph neural networks (GNNs) have become a prominent approach for developing fast, topology-aware surrogates in electric power systems, supporting tas

Reasoning Instructions Can Break Answer Decoding in Vision--Language Models

arXiv:2609.29278v1 Announce Type: cross Abstract: Chain-of-thought (CoT) instructions can distort multiple-choice VLM evaluation when a scorer appends a reasoning cue but reads answer-label logits bef

ReCalMatch:Reliability-Calibrated Semantic Guidance for Semi-Supervised Fine-Grained Recognition

arXiv:2609.29678v1 Announce Type: cross Abstract: Semi-supervised fine-grained visual recognition is highly vulnerable to overconfident pseudo-label errors: visually similar categories frequently prod

Recoverable Geographic Location Information in Earth-Observation Embeddings

arXiv:2609.29151v1 Announce Type: new Abstract: Earth-observation (EO) foundation models provide reusable embeddings, yet downstream task accuracy does not reveal whether these representations encode

Residual Correlation as a Diagnostic for Joint-Uncertainty Gains from GP Coregionalisation

arXiv:2609.30085v1 Announce Type: new Abstract: In multi-target regression, correlated targets are often coupled through multi-output Gaussian processes with an intrinsic model of coregionalisation (G

Response-state Learning for Transferable Vibrational Spectroscopic Characterization with Electron Prior

arXiv:2609.28935v1 Announce Type: new Abstract: Vibrational spectral prediction can become inaccurate when localized stereoelectronic environments perturb intermediate response states and high-risk re

RoboLDA: A Probabilistic Generative Model for Uncovering Embodied Hierarchical Structures in Voxel-based Soft Robots

arXiv:2609.29490v1 Announce Type: cross Abstract: Recent advances in robotics highlight hierarchical configurations of robot morphology, where multiple levels of functional substructures synergize to

Robots That Take Initiative: A Framework for Building and Evaluating Proactive Robots

arXiv:2609.28910v1 Announce Type: cross Abstract: Effective robot assistance beyond narrow roles and repetitive tasks requires robots to be proactive - to decide what needs to be done rather than wait

SALI: Shot-Aware Late Interaction for Cross-Shot Relation Matching in Text-to-Video Retrieval using Film-Grammar Knowledge

arXiv:2609.29721v1 Announce Type: new Abstract: Text-to-video retrieval usually represents a video clip by a single embedding. This embedding often loses important relations between people. E.g., an i

Sample-Weighted End-to-End Trace-Norm Geometry for Multitask Learning

arXiv:2609.29520v1 Announce Type: new Abstract: Multitask models combine a shared representation with task-specific outputs, but generalization bounds often control the two components separately. Such