Free Lunch in Medical Image Foundation Model Pre-training via Randomized Synthesis and Disentanglement
arXiv:2602.12317v1 Announce Type: cross Abstract: Medical image foundation models (MIFMs) have demonstrated remarkable potential for a wide range of clinical tasks, yet their development is constrained by the scarcity, heterogeneity, and high cost of large-scale annotated datasets. Here, we propose...
ForeAct: Steering Your VLA with Efficient Visual Foresight Planning
arXiv:2602.12322v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models convert high-level language instructions into concrete, executable actions, a task that is especially challenging in open-world environments. We present Visual Foresight Planning (ForeAct), a general and efficient planner that guides a VLA...
Intrinsic Credit Assignment for Long Horizon Interaction
arXiv:2602.12342v1 Announce Type: cross Abstract: How can we train agents to navigate uncertainty over long horizons? In this work, we propose {\Delta}Belief-RL, which leverages a language model's own intrinsic beliefs to reward intermediate progress. Our method utilizes the change in...
Policy4OOD: A Knowledge-Guided World Model for Policy Intervention Simulation against the Opioid Overdose Crisis
arXiv:2602.12373v1 Announce Type: cross Abstract: The opioid epidemic remains one of the most severe public health crises in the United States, yet evaluating policy interventions before implementation is difficult: multiple policies interact within a dynamic system where targeting one risk...
Reproducing DragDiffusion: Interactive Point-Based Editing with Diffusion Models
arXiv:2602.12393v1 Announce Type: cross Abstract: DragDiffusion is a diffusion-based method for interactive point-based image editing that enables users to manipulate images by directly dragging selected points. The method claims that accurate spatial control can be achieved by optimizing a single...
What does RL improve for Visual Reasoning? A Frankenstein-Style Analysis
arXiv:2602.12395v1 Announce Type: cross Abstract: Reinforcement learning (RL) with verifiable rewards has become a standard post-training stage for boosting visual reasoning in vision-language models, yet it remains unclear what capabilities RL actually improves compared with supervised fine-tuning as cold-start initialization...
Safe Reinforcement Learning via Recovery-based Shielding with Gaussian Process Dynamics Models
arXiv:2602.12444v1 Announce Type: cross Abstract: Reinforcement learning (RL) is a powerful framework for optimal decision-making and control but often lacks provable guarantees for safety-critical applications. In this paper, we introduce a novel recovery-based shielding framework that enables safe RL with...
Designing RNAs with Language Models
arXiv:2602.12470v1 Announce Type: cross Abstract: RNA design, the task of finding a sequence that folds into a target secondary structure, has broad biological and biomedical impact but remains computationally challenging due to the exponentially large sequence space and exponentially many...
Discovering Semantic Latent Structures in Psychological Scales: A Response-Free Pathway to Efficient Simplification
arXiv:2602.12575v1 Announce Type: new Abstract: Psychological scale refinement traditionally relies on response-based methods such as factor analysis, item response theory, and network psychometrics to optimize item composition. Although rigorous, these approaches require large samples and may be constrained by data...
$\mathcal{X}$-KD: General Experiential Knowledge Distillation for Large Language Models
arXiv:2602.12674v1 Announce Type: new Abstract: Knowledge Distillation (KD) for Large Language Models (LLMs) has become increasingly important as models grow in size and complexity. While existing distillation approaches focus on imitating teacher behavior, they often overlook the original learning environment...
Lamer-SSL: Layer-aware Mixture of LoRA Experts for Continual Multilingual Expansion of Self-supervised Models without Forgetting
arXiv:2602.12746v1 Announce Type: new Abstract: Despite their impressive performance, self-supervised speech models often struggle to generalize to new languages and tend to forget previously acquired knowledge during continual training. To address this, we propose Lamer-SSL, a parameter-efficient framework that integrates...
Aspect-Based Sentiment Analysis for Future Tourism Experiences: A BERT-MoE Framework for Persian User Reviews
arXiv:2602.12778v1 Announce Type: new Abstract: This study advances aspect-based sentiment analysis (ABSA) for Persian-language user reviews in the tourism domain, addressing challenges of low-resource languages. We propose a hybrid BERT-based model with Top-K routing and auxiliary losses to mitigate routing...
MentalBench: A Benchmark for Evaluating Psychiatric Diagnostic Capability of Large Language Models
arXiv:2602.12871v1 Announce Type: new Abstract: We introduce MentalBench, a benchmark for evaluating psychiatric diagnostic decision-making in large language models (LLMs). Existing mental health benchmarks largely rely on social media data, limiting their ability to assess DSM-grounded diagnostic judgments. At the...
BaziQA-Benchmark: Evaluating Symbolic and Temporally Compositional Reasoning in Large Language Models
arXiv:2602.12889v1 Announce Type: new Abstract: We present BaziQA-Benchmark, a standardized benchmark for evaluating symbolic and temporally compositional reasoning in large language models. The benchmark is derived from 200 professionally curated, multiple-choice problems from the Global Fortune-teller Competition (2021--2025), where each...
ViMedCSS: A Vietnamese Medical Code-Switching Speech Dataset & Benchmark
arXiv:2602.12911v1 Announce Type: new Abstract: Code-switching (CS), which is when Vietnamese speech uses English words like drug names or procedures, is a common phenomenon in Vietnamese medical communication. This creates challenges for Automatic Speech Recognition (ASR) systems, especially in low-resource...
Curriculum Learning and Pseudo-Labeling Improve the Generalization of Multi-Label Arabic Dialect Identification Models
arXiv:2602.12937v1 Announce Type: new Abstract: Being modeled as a single-label classification task for a long time, recent work has argued that Arabic Dialect Identification (ADI) should be framed as a multi-label classification task. However, ADI remains constrained by the availability...
Evaluating the Homogeneity of Keyphrase Prediction Models
arXiv:2602.12989v1 Announce Type: new Abstract: Keyphrases which are useful in several NLP and IR applications are either extracted from text or predicted by generative models. Contrarily to keyphrase extraction approaches, keyphrase generation models can predict keyphrases that do not appear...
TraceBack: Multi-Agent Decomposition for Fine-Grained Table Attribution
arXiv:2602.13059v1 Announce Type: new Abstract: Question answering (QA) over structured tables requires not only accurate answers but also transparency about which cells support them. Existing table QA systems rarely provide fine-grained attribution, so even correct answers often lack verifiable grounding,...
Exploring a New Competency Modeling Process with Large Language Models
arXiv:2602.13084v1 Announce Type: new Abstract: Competency modeling is widely used in human resource management to select, develop, and evaluate talent. However, traditional expert-driven approaches rely heavily on manual analysis of large volumes of interview transcripts, making them costly and prone...
From sunblock to softblock: Analyzing the correlates of neology in published writing and on social media
arXiv:2602.13123v1 Announce Type: new Abstract: Living languages are shaped by a host of conflicting internal and external evolutionary pressures. While some of these pressures are universal across languages and cultures, others differ depending on the social and conversational context: language...
OpenLID-v3: Improving the Precision of Closely Related Language Identification -- An Experience Report
arXiv:2602.13139v1 Announce Type: new Abstract: Language identification (LID) is an essential step in building high-quality multilingual datasets from web data. Existing LID tools (such as OpenLID or GlotLID) often struggle to identify closely related languages and to distinguish valid natural...
HyperMLP: An Integrated Perspective for Sequence Modeling
arXiv:2602.12601v1 Announce Type: cross Abstract: Self-attention is often viewed as probabilistic query-key lookup, motivating designs that preserve normalized attention scores and fixed positional semantics. We advocate a simpler and more unified perspective: an autoregressive attention head can be viewed as...
VimRAG: Navigating Massive Visual Context in Retrieval-Augmented Generation via Multimodal Memory Graph
arXiv:2602.12735v1 Announce Type: cross Abstract: Effectively retrieving, reasoning, and understanding multimodal information remains a critical challenge for agentic systems. Traditional Retrieval-augmented Generation (RAG) methods rely on linear interaction histories, which struggle to handle long-context tasks, especially those involving information-sparse yet...
The Appeal and Reality of Recycling LoRAs with Adaptive Merging
arXiv:2602.12323v1 Announce Type: new Abstract: The widespread availability of fine-tuned LoRA modules for open pre-trained models has led to an interest in methods that can adaptively merge LoRAs to improve performance. These methods typically include some way of selecting LoRAs...
Wireless TokenCom: RL-Based Tokenizer Agreement for Multi-User Wireless Token Communications
arXiv:2602.12338v1 Announce Type: new Abstract: Token Communications (TokenCom) has recently emerged as an effective new paradigm, where tokens are the unified units of multimodal communications and computations, enabling efficient digital semantic- and goal-oriented communications in future wireless networks. To establish...
Continuous Diffusion Models Can Obey Formal Syntax
arXiv:2602.12468v1 Announce Type: new Abstract: Diffusion language models offer a promising alternative to autoregressive models due to their global, non-causal generation process, but their continuous latent dynamics make discrete constraints -- e.g., the output should be a JSON file that...
Regularized Meta-Learning for Improved Generalization
arXiv:2602.12469v1 Announce Type: new Abstract: Deep ensemble methods often improve predictive performance, yet they suffer from three practical limitations: redundancy among base models that inflates computational cost and degrades conditioning, unstable weighting under multicollinearity, and overfitting in meta-learning pipelines. We...
Tight Bounds for Logistic Regression with Large Stepsize Gradient Descent in Low Dimension
arXiv:2602.12471v1 Announce Type: new Abstract: We consider the optimization problem of minimizing the logistic loss with gradient descent to train a linear model for binary classification with separable data. With a budget of $T$ iterations, it was recently shown that...
A Theoretical Analysis of Mamba's Training Dynamics: Filtering Relevant Features for Generalization in State Space Models
arXiv:2602.12499v1 Announce Type: new Abstract: The recent empirical success of Mamba and other selective state space models (SSMs) has renewed interest in non-attention architectures for sequence modeling, yet their theoretical foundations remain underexplored. We present a first-step analysis of generalization...
Analytical Results for Two Exponential Family Distributions in Hierarchical Dirichlet Processes
arXiv:2602.12527v1 Announce Type: new Abstract: The Hierarchical Dirichlet Process (HDP) provides a flexible Bayesian nonparametric framework for modeling grouped data with a shared yet unbounded collection of mixture components. While existing applications of the HDP predominantly focus on the Dirichlet-multinomial...