arXiv Machine Learning
Jun 8
The Identity Trap in EEG Foundation Models: A Diagnostic Audit
arXiv:2606. 06647v1 Announce Type: new Abstract: Objective.
Fine-tuning and adaptation
LoRA, PEFT, instruction tuning and domain adaptation — adapting a pretrained model without paying to train one.
arXiv Machine Learning
Jun 8
Inheritance Between Feedforward and Convolutional Networks via Model Projection
arXiv:2602. 06245v2 Announce Type: replace-cross Abstract: Neural-network techniques are often transferred across architecture families by analogy, but such transfer is valid only when the assumptions required by a technique are preserved.
arXiv AI
Jun 8
The Fine-Tuning Trap: Evaluating Negative Transfer and the Role of PEFT in Sub-1B Mathematical Reasoning
arXiv:2606. 06920v1 Announce Type: cross Abstract: Deploying Small Language Models (SLMs) on edge devices requires efficient fine-tuning strategies that adapt models to new tasks without degrading their general capabilities.
arXiv Machine Learning
Jun 8
A Dynamic Self-Evolving Extraction System
arXiv:2603. 06915v2 Announce Type: replace-cross Abstract: The extraction of structured information from raw text is a fundamental component of many NLP applications, including document retrieval, ranking, and relevance estimation.
arXiv AI
Jun 8
SafeGene: Reusable Adapters for Transferable Safety Alignment
arXiv:2606. 06519v1 Announce Type: new Abstract: Open-weight LLMs are increasingly fine-tuned into customized assistants, but downstream fine-tuning can weaken safety alignment and make models more vulnerable to malicious prompts, even when the training data is not intentionally harmful.
arXiv AI
Jun 8
MatterDoor: Sampling Zero-shot Spatio-semantic Priors using Generative Models
arXiv:2510. 11014v2 Announce Type: replace-cross Abstract: Autonomous robots often view rooms only partially, through a doorway, where the walls and scene structure hide the geometry and task-relevant semantics needed for safe navigation and goal-directed action.
arXiv AI
Jun 8
HKJudge: A Legal Discourse-Annotated Corpus for Interpreting What Courts Find, How They Reason, and What They Rule
arXiv:2606. 06679v1 Announce Type: cross Abstract: Court judgments are central to legal practice and jurisprudence, yet discourse analysis of Hong Kong judgments has received limited attention, owing largely to the absence of expert-annotated corpora.
arXiv AI
Jun 8
SpectCount: Spectrotemporal Counting via Synthetic Signals Improves Large Audio Language Models
arXiv:2606. 06907v1 Announce Type: cross Abstract: Large audio language models (LALMs) extend large language models with an audio encoder and large-scale audio data.
arXiv Machine Learning
Jun 8
Federated Foundation Models over Vehicular Networks
arXiv:2606. 06786v1 Announce Type: new Abstract: This paper presents a forward-looking vision for integrating the emerging multi-modal multi-task federated foundation models (M3T FedFMs) into vehicular networks, with the goal of unifying the expressive power of multi-modal multi-task foundation models (M3T FMs) with the privacy-preserving and distributed learning capabilities of federated learning (FL).
arXiv AI
Jun 8
Just-In-Time Reinforcement Learning: Continual Learning in LLM Agents Without Gradient Updates
arXiv:2601. 18510v2 Announce Type: replace-cross Abstract: While Large Language Model (LLM) agents excel at general tasks, they inherently struggle with continual adaptation due to the frozen weights after deployment.
arXiv AI
Jun 8
ReclAIm: A Multi-Agent Framework for Monitoring and Correcting Performance Decline in Medical Imaging AI
arXiv:2510. 17004v2 Announce Type: replace-cross Abstract: Purpose: To develop and evaluate a multi-agent framework (ReclAIm) for automated monitoring, detection, and correction of performance decline in medical image classification models.
arXiv Machine Learning
Jun 8
AutoTool: Dynamic Tool Selection and Integration for Agentic Reasoning
arXiv:2512. 13278v2 Announce Type: replace-cross Abstract: Agentic reinforcement learning has advanced large language models (LLMs) to reason through long chain-of-thought trajectories while interleaving external tool use.
arXiv Machine Learning
Jun 8
RhinoVLA Technical Report
arXiv:2606. 07383v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have shown strong potential for robotic manipulation, but real-time deployment on edge hardware remains challenging.
arXiv AI
Jun 8
PandaAI: A Practical Agent CQ2 for Neuro-symbolic Data Analysis And Integrated Decision-Making in Quantitative Finance
arXiv:2606. 06823v1 Announce Type: cross Abstract: While deep learning has excelled in various domains, its application to sequential decision-making in finance remains challenging due to the low Signal-to-Noise Ratio (SNR) and non-stationarity of financial data.
arXiv AI
Jun 8
Whisper Hallucination Detection and Mitigation via Hidden Representation Steering and Sparse AutoEncoders
arXiv:2606. 07473v1 Announce Type: cross Abstract: Whisper, a widely adopted ASR model, is known to suffer from hallucinations - coherent transcriptions generated for non-speech audio entirely disconnected from the input.
arXiv Machine Learning
Jun 8
RASFT: Rollout-Adaptive Supervised Fine-Tuning for Reasoning
arXiv:2606. 07006v1 Announce Type: new Abstract: Supervised fine-tuning (SFT) is a prevailing method for adapting large language models to reasoning tasks by imitating offline expert demonstrations, often treating a single expert trajectory as the target behavior.
Hugging Face Trending Papers
Jun 8
From Hazard Functions to Language Space: Cox-Supervised Distillation of Survival Risk into a Large Language Model
We investigate whether information about time-to-event risk estimated by a Cox proportional hazards model can be transferred into a generative large language model. We propose a text-based survival modelling pipeline in which structured clinical covariates are converted into text prompts and a Qwen-based large language model is fine-tuned to generate patient-specific survival risk using Cox model predictions as a training target.
arXiv AI
Jun 6
Code2LoRA: Hypernetwork-Generated Adapters for Code Language Models under Software Evolution
arXiv:2606. 06492v1 Announce Type: cross Abstract: Code language models need repository-level context to resolve imports, APIs, and project conventions.
arXiv AI
Jun 6
VASO: Formally Verifiable Self-Evolving Skills for Physical AI Agents
arXiv:2606. 05395v1 Announce Type: cross Abstract: Reusable robot skills are becoming the basic units through which embodied agents turn open-ended instructions into long-horizon physical behavior.
arXiv AI
Jun 6
Better Literary Translation: A Multi-Aspect Data Generation and LLM Training Approach
arXiv:2606. 05924v1 Announce Type: cross Abstract: Literary translation poses unique challenges due to the scarcity of high-quality annotated data and the need to balance expression fluency with literary effect.