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Monday 19 October
- PaperPFedQFT: Personalized Federated Quantum-Inspired Fine-Tuning for Medical Large Language Models
Medical data remain fragmented across institutional silos because of privacy, governance, and ownership constraints. Federated learning enables medical institutions to ad
- PaperEvidence Sufficiency and Model Comparisons in MexRegQA: An Item-Level Audit of Mexican-Spanish Regulatory QA
Similarity-gated coverage does not establish that retrieved evidence contains the facts needed to answer a question. We audit Mexican-Spanish financial-regulatory QA and
- PaperCausal Humility: Governing the Authority of Fairness Claims Under Causal Uncertainty
AI systems increasingly shape consequential decisions in employment, lending, healthcare, and public services, making fairness an important problem for auditing and gover
- PaperWhose Credential Is It? How Owner Attribution in Agent MemoryShapes Cross-User Account Misuse
Shared long-term memory lets an LLM agent serving one user inadvertently retrieve another user's credentials, but it is unclear when such exposure leads to actual harm. W
- PaperPredictive Bandit Curriculum Reinforcement Learning via Gradient-Based Sample Group Discovery
Curriculum learning, which organizes training samples according to their learning priority, has been widely adopted in reinforcement learning to improve training efficien
- PaperFrom Black Box to Controller: Inference-Time Steering of LLM via Feature Amplification
Inference-time steering is crucial for deploying Large Language Models (LLMs) in real-world applications, where they must flexibly adjust behavior preferences. For instan
- PaperStochastic Tracking of Drifting Affine Fixed Points
Linear stochastic approximation (SA) is widely used to estimate fixed points from noisy observations, but most finite-time analyses assume that the underlying operator re
- PaperCVaR-RMD: CVaR Selection Pressure for Robust Metaheuristic Discovery
Large language models have recently been used to discover heuristics through iterative program search, offering a promising approach to automated algorithm design. Howeve
- PaperMulti-View Structural Representations for Physically-Consistent TeX Generation
Infrared and visible images provide complementary cues for low-light image generation, and physics-based methods can better exploit this complementarity. However, existin
- PaperToolOPD: Credit-Aware On-Policy Distillation for Tool-Use Agents
On-policy distillation (OPD) enhances the capabilities of small language agents by providing dense, token-level supervision from a teacher model on student-generated traj
- PaperProgress-Guided Preference Generation for Aligning Generative Control Policies
Generative policies have achieved strong performance in imitation learning tasks, but their success is often constrained by the limited availability of expert demonstrati
- PaperMT-CC: Multi-Group Temperature Scaling for Asymmetric Calibration Behavior in Class-Incremental Learning
As deep neural networks are required to continuously adapt to evolving data, class-incremental learning (CIL) has become an active research area. However, most existing w
- PaperWhen Safety Fails Collectively: Robust Alignment Against Harmful Fine-Tuning via Joint Weight Perturbations
Harmful fine-tuning can rapidly erode the safety alignment of large language models, creating substantial risks when aligned models are adapted to downstream tasks. Exist
- PaperBitFlat: Error-Localized Bitstream Design for Robust Diffusion Image Compression
Zero-shot diffusion image compression based on reverse channel coding achieves high perceptual quality at low bitrates without retraining, yet its bitstream remains vulne
- PaperRxGS: Relightable Gaussian Stylization via BRDF Decomposition
Reference-based 3D scene stylization transfers the appearance of a reference image onto a reconstructed 3D scene while preserving scene geometry. Recent methods perform t
- PaperLOOP: Recovery-Aligned Iterative Layer Pruning via On-Policy Distillation
Layer-level pruning is attractive for large language model (LLM) deployment as it reduces the model size while preserving a dense architecture that can be efficiently exe
- PaperCross-Pollination Retrieval: Finding Transferable Ideas Across Fields in Scientific Literature
Many scientific advances come from cross-pollination, carrying an idea from one field over to a problem in another. Yet retrieving papers across fields remains underexplo
- PaperNeither Over- nor Under-Constrained: Evaluating LLM Personalization under a Constraint Qualification Audit
Accurate evaluation of LLM personalization is hindered by current evaluation paradigms that over- or under-constrain the response space, yielding frequent false rejection
- PaperLIRQuant: An Efficient Locally Isolated Rotation Quantization Method for Large Language Models
Post-Training Quantization (PTQ) enables efficient deployment of Large Language Models (LLMs), yet activation outliers remain a key challenge for low-bit quantization. Ex
- PaperHyperTaxa: Multiscale Genome Representations for Generalized Microbial Taxonomic Inference
Reliable microbial taxonomic inference is challenged by the rapid growth of newly sequenced organisms and incomplete reference coverage. While alignment- and database-dri
- PaperArbitrage-Free Implied Volatility Surface Reconstruction via Additive Martingales
This work focuses on reconstructing a continuous implied volatility (IV) surface from a small number of option quotes, a fundamental task for option pricing and risk mana
- PaperFrechet Forcing: Training Long-Horizon Streaming World Models from Short Clips
Streaming video world models generate the future chunk by chunk, conditioned on their own past and a stream of actions. Trained on short clips, they drift once a rollout
- PaperSpaRV: Sparse Radiance Voxels for Scalable Geometrically Consistent LiDAR-Visual Mapping and Rendering
Robotic simulation, navigation, and inspection need photorealistic and geometrically accurate maps. Radiance fields achieve photorealism, but building them from robot dat
- PaperPoSTCache: From Forecasting to Postdictive Smoothing for Revisable Diffusion Caching
Diffusion and flow matching models achieve impressive visual generation quality but remain computationally expensive due to iterative sampling. Caching-based acceleration
- PaperCan Metadata Fix the Gauge? Calibration Turns Sparse Multi-Source Learning from Sparse PCA into Sparse Mean Recovery
Source labels tell us where a sample came from, but not how that source oriented its coordinates. In a sparse Gaussian multi-source model with source-specific sign gauges
- PaperKnowledge Manifold Optimization for Scientific Discovery
The rapid expansion and specialization of scientific literature make it increasingly difficult to identify not only what is known, but where new and still supportable kno
- PaperFluidGen: Physics-Aware Fluid Video Generation via Motion-Guided Post-Training
Video generation models produce visually compelling motion but systematically fail on fluid phenomena, including smoke, fire, and explosion debris, where outputs lack coh
- PaperBeyond Leaderboards: A Method for Application-Specific Capability Profiling of Large Language Models
Public leaderboards rank large language models (LLMs) in general, but an engineer has to choose a model for a specific application, architecture and cost. This paper pres
- PaperA "feature ODE" describing the learning behavior of shallow MLPs on simple functions
We study the gradient flow training dynamics of two-layer multi-layer perceptrons (MLPs) on anisotropic Gaussian data. Even in this simple setting, solving the dynamics i
- PaperOPDArena: Understanding Learning and Forgetting in On-Policy Distillation
On-policy distillation (OPD) is increasingly used for language model post-training, yet how teacher supervision shapes learning and forgetting remains unclear. We present
- PaperConsistency Training Suppresses Cue Following Without Teaching Cue Selectivity
Language models often change answers because of a cue, a hint such as "I believe the answer is B" that gives no valid evidence. Consistency training (CT) trains a model t
- PaperLatent Projection for Latent Planning
Latent world models let an agent plan in latent space. The planner searches for an action sequence that minimizes a cost, and that cost is often the $\ell_2$ distance bet
- PaperInteractAgent: Agentic Human Motion Interaction with Memory-Augmented Reflection
Long-horizon human-scene interaction requires coordinated spatial reasoning, physical feasibility, and the ability to recover from compounding execution errors. Text-driv
- PaperSpherical Fixed-Point Reasoners: Adaptive Loop Halting on the Hypersphere
Looped (weight-tied) transformers enable adaptive computation by allocating more iterations to harder inputs. Fixed-Point Reasoners (FPRM) achieve this with a damped fixe
- PaperNegation without Confusion: Decomposing Bias and Recomposing Style in Text Embeddings for Negation-aware Image Generation
Negation-aware image generation remains challenging for text-to-image diffusion models, which often struggle with negation due to implicit linguistic biases that are deep
- PaperSampling of Signals on Multigraphs: From Removable and Uniqueness sets to Spectral Proxies
In this paper, we study the sampling of bandlimited signals on multigraphs, where several graphs with different shift operators are defined on the same set of nodes. Sinc
- PaperVisual Memory and Textual Alignment for Cross-Modal Few-Shot Segmentation
Few-shot segmentation (FSS) aims to segment target objects with limited annotated examples. Recent studies have begun to explore large foundation models to improve genera
- PaperThink, Compress, Answer: Reinforcement Learning for Multimodal Grounding via Reasoning Compression
Extended reasoning has substantially improved multimodal large language models (MLLMs) on tasks requiring compositional and relational inference. However, multimodal grou
- PaperACorD: Adaptive Correspondence Discovery for Medical Image Registration
Medical image registration is a fundamental task for aligning anatomical structures across images. Exhaustively searching for point-wise correspondences is prohibitively
- PaperTNVD-SC: Diagnosing Scan Context Failures in Forests with Terrain-Normalized Vertical Distributions
Long-term LiDAR place recognition in forests is difficult because repetitive vegetation and uneven terrain create severe structural aliasing. We diagnose Scan Context (SC
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