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Bridging the Knowledge-Prediction Gap in LLMs on Multiple-Choice Questions

arXiv:2509.23782v4 Announce Type: replace Abstract: While large language models (LLMs) perform strongly on diverse tasks, their trustworthiness is limited by erratic behavior that is unfaithful to the

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Bridging Topology and Deep Representation Learning: A TDA-ViT Fusion Model for Four-Class Brain Tumor Classification

DGX agent

arXiv:2606.00927v1 Announce Type: new Abstract: Accurate brain tumor classification from magnetic resonance imaging (MRI) is a key requirement for early diagnosis and clinical decision-making. Vision

researcharxiv-cs-cv

2 Jun 2026

Byte Pair Encoding for Efficient Time Series Forecasting

arXiv:2505.14411v4 Announce Type: replace Abstract: Existing time series tokenization methods predominantly encode a constant number of samples into individual tokens. This inflexible approach can gen

CA-BED: Conversation-Aware Bayesian Experimental Design

arXiv:2606.01182v1 Announce Type: cross Abstract: Large Language Models (LLMs) excel at static reasoning tasks, yet their performance often degrades in interactive scenarios where information must be

Can Predicted Dynamics Exist in the Physical World?

arXiv:2606.00089v1 Announce Type: cross Abstract: Predictive Physical AI systems output state rollouts, action chunks, and latent plans, yet a low root-mean-square error (RMSE) does not imply that a p

CANARY: Zero-Label Detection of Fine-Tuning Contamination in Language Models

arXiv:2606.01695v1 Announce Type: new Abstract: Adversaries can implant latent harmful behavior by poisoning as few as 1% of fine-tuning examples. The contamination is invisible to every output-level

Canonicalized Stable-List Replay for Private Federated Continual Learning over Language-Model Embeddings

arXiv:2606.00426v1 Announce Type: new Abstract: Federated continual learning (FCL) lets distributed clients adapt language-model heads to evolving NLP tasks without sharing raw text. Under user-level

CARE-RL: Capability-Aware Reinforcement Learning for Mitigating Cross-Domain Conflicts

arXiv:2606.00609v1 Announce Type: cross Abstract: Reinforcement learning (RL) with verifiable rewards has achieved strong progress in reasoning-oriented LLMs, but extending it to multi-domain RL remai

CARES: Context-Aware Resolution Selector for VLMs

arXiv:2510.19496v3 Announce Type: replace-cross Abstract: Large vision-language models (VLMs) commonly process images at native or high resolution to remain effective across tasks. This inflates visua

Causal Density Functions

arXiv:2606.00754v1 Announce Type: cross Abstract: We introduce causal density functions: Radon-Nikodym derivatives that compare interventional laws to observational laws and therefore act as local den

CEON: Circular Economy Ontology Network

arXiv:2606.02253v1 Announce Type: new Abstract: Increasing the circularity of resource use in our society has been recognized as a path to sustainability, i.e., transitioning into a more circular econ

Certificate-Guided Evaluation of Reinforcement Learning Generalization

arXiv:2606.00840v1 Announce Type: new Abstract: This work presents a logic-driven framework to evaluate the performance of reinforcement learning (RL) algorithms in their ability to generalize to unse

Challenger at MultiPRIDE: Is It Hate Speech or Reclaimed?

arXiv:2606.01298v1 Announce Type: new Abstract: The spread of hate speech has become increasingly harmful in modern digital environments, particularly on social networking platforms. While recent adva

CHAM-net: A Contrastive Hierarchical Adaptive Meta-network for Robust Global Methane Flux Prediction

arXiv:2606.00338v1 Announce Type: new Abstract: Methane is a potent greenhouse gas that significantly contributes to global warming. However, accurately estimating global methane emissions and consump

Characterizing the Effect of Noise in Language Generation in the Limit

arXiv:2601.21237v2 Announce Type: replace-cross Abstract: Kleinberg and Mullainathan recently proposed a formal framework for studying the phenomenon of language generation, called language generation

Characterizing Web Search in The Age of Generative AI

arXiv:2510.11560v2 Announce Type: replace-cross Abstract: The advent of LLMs has given rise to generative search, a new search paradigm in which LLMs retrieve information from the web related to a que

ChatUMM: Robust Context Tracking for Conversational Interleaved Generation

arXiv:2602.06442v2 Announce Type: replace Abstract: Unified multimodal models (UMMs) have achieved remarkable progress yet remain constrained by a single-turn interaction paradigm, effectively functio

Chunking Methods on Retrieval-Augmented Generation - Effectiveness Evaluation Against Computational Cost and Limitations

arXiv:2606.00881v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) has demonstrated significant capabilities in enhancing the performance of Large Language Models (LLMs). One of the

ChurnNet: A Optimized Modern AI for Churn Prediction

arXiv:2606.00169v1 Announce Type: cross Abstract: Increased competition and the growing similarity of products and services offered by retailers have lowered the barriers for customers to switch to co

ChWDTA: Channel-wise Wavelet-Domain Transformer Attention and Entropy Modeling for Learned Image Compression

arXiv:2606.00111v1 Announce Type: cross Abstract: State-of-the-art learned image compression (LIC) schemes are increasingly based on hybrid CNN-transformer architectures. To further improve rate-disto

CloSE: A Geometric Shape-Agnostic Cloth State Representation

arXiv:2504.05033v3 Announce Type: replace-cross Abstract: Cloth manipulation is a difficult problem mainly because of the non-rigid nature of cloth, which makes a good representation of deformation es

Co-training with Ego-centric Video and Demonstration for Robot Navigation Task

arXiv:2606.01951v1 Announce Type: new Abstract: Vision-language-action (VLA) models are promising for diverse robotic tasks, but their performance heavily depends on large-scale high-quality training

researcharxiv-cs-ro

Cognitive-Linguistic Indicators of Depression in Online Communities: Analysed by DistilBERT and Holographic Reduced Representation

arXiv:2606.00026v1 Announce Type: new Abstract: This paper investigates whether combining cognitively grounded linguistic features with transformer-based embeddings improves automated detection of dep

CoilDrop-MRI: Self-supervised physics-guided MRI reconstruction with coil dropout

arXiv:2606.00100v1 Announce Type: cross Abstract: Self-supervised deep learning-based methods have shown great promise for accelerated magnetic resonance imaging (MRI) reconstruction, achieving high i

Computation-Aware Kalman Filtering with Model Selection for Neural Dynamics

arXiv:2606.01468v1 Announce Type: cross Abstract: Due to their explicit priors and ability to model uncertainty, Bayesian methods have played a major role in dynamical latent variable modeling of sing

Concept Heterogeneity-aware Representation Steering

arXiv:2603.02237v2 Announce Type: replace-cross Abstract: Representation steering offers a lightweight mechanism for controlling the behavior of large language models (LLMs) by intervening on internal

Conditioned free-energy density of proteins using unbalanced solutions to constraint satisfaction problems

arXiv:2606.01329v1 Announce Type: new Abstract: We show that computing the log-partition function (free-energy) of conditioned inhomogeneous Curie--Weiss spin Hamiltonians reduces to an unbalanced 2 o

Confidence-Adaptive SwiGLU for Mixture-of-Experts

arXiv:2606.00761v1 Announce Type: cross Abstract: SwiGLU has become a standard gated activation in modern Transformer MLPs, yet its gate sharpness -- the smoothness and selectivity of the gating funct

Consistency Deep Equilibrium Models

arXiv:2602.03024v2 Announce Type: replace-cross Abstract: Deep Equilibrium Models (DEQs) have emerged as a powerful paradigm in deep learning, offering the ability to model infinite-depth networks wit

Construction of Historical Knowledge Graphs Based on BERT and Graph Neural Networks

arXiv:2606.01747v1 Announce Type: cross Abstract: Through digital humanities research and scale-up historical data analysis, a significant amount of traditional historical text is converted into struc

Context-aware child-directed speech detection from long-form recordings

arXiv:2606.01134v1 Announce Type: cross Abstract: Automatically distinguishing child-directed speech from adult-directed speech in long-form recordings is key to scalable analyses of children's langua

Continual Learning as a Multiphase Moving-Boundary Problem

arXiv:2606.01863v1 Announce Type: new Abstract: Continual learning struggles to balance retaining past knowledge with absorbing new tasks. Stefan-CL elegantly resolves this stability-plasticity dilemm

Continuous Reasoning for Vision-Language-Action

arXiv:2606.00229v1 Announce Type: cross Abstract: Natural language is a powerful reasoning medium for language and vision-language models, but it is mismatched to the granularity of continuous control

Contrastive meta-domain adaptation for robust skin lesion classification across clinical and acquisition conditions

arXiv:2602.19857v2 Announce Type: replace Abstract: Deep learning models for dermatological image analysis remain sensitive to acquisition variability and domain-specific visual characteristics, leadi

Convex Distance Operator Transport: A Convex and Geometry-Preserving Formulation

arXiv:2606.02047v1 Announce Type: cross Abstract: We introduce Convex Distance Operator Transport (CDOT), the first convex optimal transport framework that aligns distributions across heterogeneous do

CORE-MTL: Rethinking Gradient Balancing via Causal Orthogonal Representations

arXiv:2606.02221v1 Announce Type: new Abstract: Multi-task learning (MTL) aims to construct a joint model for multiple tasks by sharing a common representation across domains. To achieve this goal, ex

Cost-Aware Diffusion Draft Trees for Speculative Decoding

arXiv:2606.01813v1 Announce Type: new Abstract: Speculative decoding accelerates inference by having a lightweight drafter propose tokens verified in parallel by the target language model. Block diffu

Counterfactual Intervention Feature Transfer for Visible-Infrared Person Re-identification

arXiv:2208.00967v4 Announce Type: replace Abstract: Graph-based models have achieved great success in person re-identification tasks recently, which compute the graph topology structure (affinities) a

Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation

arXiv:2602.05217v2 Announce Type: replace Abstract: Cross-Domain Few-Shot Segmentation aims to segment categories in data-scarce domains conditioned on a few exemplars. Typical methods first establish

Cross-lingual Self-Consistency for Multilingual Reasoning with Language Models

arXiv:2606.01464v1 Announce Type: new Abstract: Despite expanding their multilingual coverage, the advanced reasoning capabilities of LLMs remain largely confined to a few high-resource languages like

CURP: Codebook-based Continuous User Representation for Personalized Generation with LLMs

arXiv:2602.00742v2 Announce Type: replace Abstract: User modeling characterizes individuals through their preferences and behavioral patterns to enable personalized simulation and generation with Larg

DAGGER: Gradient-Free Construction of Transiently Amplifying Networks under Hard Connectivity Constraints

arXiv:2606.01227v1 Announce Type: new Abstract: Many networks not only support but also rely on transient non-normal amplification, an orders-of-magnitude increase in the activity of an otherwise stab

DAPD: Dependency-Aware Parallel Decoding via Attention for Diffusion LLMs

arXiv:2603.12996v2 Announce Type: replace Abstract: Parallel decoding for Diffusion LLMs (dLLMs) is difficult because each denoising step provides only token-wise marginal distributions, while unmaski

DarkVesselNet: Multi-Modal Remote Sensing and Trajectory Reasoning for Dark Vessel Detection

arXiv:2606.00445v1 Announce Type: cross Abstract: Dark vessel detection requires fusing what vessels report through AIS with what satellites observe through radar and optical sensors. DarkVesselNet is

Data-Driven Spectral Prediction for Accelerating Large-Scale Electronic Structure Calculations

arXiv:2606.00401v1 Announce Type: cross Abstract: Simulating large molecular systems comprising thousands of atoms requires highly scalable methodologies. While modern Density Functional Theory (DFT)

Data Enrichment for Symbolic Regression Using Diffusion Models

arXiv:2606.00988v1 Announce Type: new Abstract: Symbolic regression (SR) offers a route to scientific discovery by converting observations into interpretable governing equations. However, despite its

@DavidSacks If Trump really were 'the most pro-innovation president we’ve ever had' he would not attempt to cut research budgets by half.

Yann LeCun criticized a claim that Trump is the most pro-innovation president by pointing out that proposed cuts to research budgets would contradict genuine support for innovation. The post engages w

researchyann-lecun--x

DeblurNVS: Geometric Latent Diffusion for Novel View Synthesis from Sparse Motion-Blurred Images

arXiv:2606.01315v1 Announce Type: new Abstract: Novel view synthesis (NVS) is a fundamental problem in computer vision and graphics. Recent advances in neural radiance fields (NeRF), 3D Gaussian Splat