research

Before You Interpret the Profile: Validity Scaling for LLM Metacognitive Self-Report

arXiv:2604.17707v1 Announce Type: new Abstract: Clinical personality assessment screens response validity before interpreting substantive scales. LLM evaluation does not. We apply the validity scaling

Research

Beyond Binary Contrast: Modeling Continuous Skeleton Action Spaces with Transitional Anchors

DGX agent

arXiv:2604.17914v1 Announce Type: new Abstract: Self-supervised contrastive learning has emerged as a powerful paradigm for skeleton-based action recognition by enforcing consistency in the embedding

researcharxiv-cs-cv

21 Apr 2026

Beyond Black-Box Labels: Interpretable Criteria for Diagnosing SubjectiveNLP Tasks

arXiv:2604.17022v1 Announce Type: new Abstract: Subjective NLP datasets typically aggregate annotator judgments into a single gold label, making it difficult to diagnose whether disagreement reflects

Beyond Fine-Tuning: In-Context Learning and Chain-of-Thought for Reasoned Distractor Generation

arXiv:2604.17574v1 Announce Type: new Abstract: Distractor generation (DG) remains a labor-intensive task that still significantly depends on domain experts. The task focuses on generating plausible y

Beyond Static Benchmarks: Synthesizing Harmful Content via Persona-based Simulation for Robust Evaluation

arXiv:2604.17020v1 Announce Type: new Abstract: Static benchmarks for harmful content detection face limitations in scalability and diversity, and may also be affected by contamination from web-scale

Beyond the Failures: Rethinking Foundation Models in Pathology

arXiv:2510.23807v5 Announce Type: replace-cross Abstract: Despite their successes in vision and language, foundation models have stumbled in pathology, revealing low accuracy, instability, and heavy c

Beyond URLs: Metadata Diversity and Position for Efficient LLM Pretraining

arXiv:2511.21613v2 Announce Type: replace Abstract: Incorporating metadata in Large Language Models (LLMs) pretraining has recently emerged as a promising approach to accelerate training. However prio

Beyond Verifiable Rewards: Rubric-Based GRM for Reinforced Fine-Tuning SWE Agents

arXiv:2604.16335v1 Announce Type: new Abstract: Despite recent progress in Large Language Model (LLM) Agents for Software Engineering (SWE) tasks, end-to-end fine-tuning typically relies on verifiable

BhashaSutra: A Task-Centric Unified Survey of Indian NLP Datasets, Corpora, and Resources

arXiv:2604.18423v1 Announce Type: new Abstract: India's linguistic landscape, spanning 22 scheduled languages and hundreds of marginalized dialects, has driven rapid growth in NLP datasets, benchmarks

Bilinear Input Modulation for Mamba: Koopman Bilinear Forms for Memory Retention and Multiplicative Computation

arXiv:2604.17221v1 Announce Type: cross Abstract: Selective State Space Models (SSMs), notably Mamba, employ diagonal state transitions that limit both memory retention and bilinear computational capa

BioVLM: Routing Prompts, Not Parameters, for Cross-Modality Generalization in Biomedical VLMs

arXiv:2604.17629v1 Announce Type: new Abstract: Pretrained biomedical vision-language models (VLMs) such as BioMedCLIP perform well on average but often degrade on challenging modalities where inter-c

Bounded Graph Clustering with Graph Neural Networks

arXiv:2512.05623v2 Announce Type: replace Abstract: In community detection, many methods require the user to specify the number of clusters in advance since an exhaustive search over all possible valu

Brain-CLIPLM: Decoding Compressed Semantic Representations in EEG for Language Reconstruction

arXiv:2604.16370v1 Announce Type: new Abstract: Decoding natural language from non-invasive electroencephalography (EEG) remains fundamentally limited by low signal-to-noise ratio and restricted infor

Bridging Coarse and Fine Recognition: A Hybrid Approach for Open-Ended Multi-Granularity Object Recognition in Interactive Educational Games

arXiv:2604.16785v1 Announce Type: new Abstract: Recent advances in Multimodal Large Language Models (MLLMs) have enabled open-ended object recognition, yet they struggle with fine-grained tasks. In co

Calibrating Model-Based Evaluation Metrics for Summarization

arXiv:2604.17200v1 Announce Type: new Abstract: Recent advances in summary evaluation are based on model-based metrics to assess quality dimensions, such as completeness, conciseness, and faithfulness

CamPVG: Camera-Controlled Panoramic Video Generation with Epipolar-Aware Diffusion

arXiv:2509.19979v2 Announce Type: replace Abstract: Recently, camera-controlled video generation has seen rapid development, offering more precise control over video generation. However, existing meth

Central Limit Theorems for Asynchronous Averaged Q-Learning

arXiv:2509.18964v3 Announce Type: replace Abstract: This paper establishes central limit theorems for Polyak-Ruppert averaged Q-learning under asynchronous updates. We prove a non-asymptotic central l

Centre manifold theorem for maps along manifolds of fixed points

arXiv:2604.18202v1 Announce Type: cross Abstract: We prove a centre manifold theorem for a map along a manifold-with-boundary of fixed points, and provide an application to the study of gradient desce

Chaos-Enhanced Prototypical Networks for Few-Shot Medical Image Classification

arXiv:2604.17300v1 Announce Type: cross Abstract: The scarcity of labeled clinical data in oncology makes Few-Shot Learning (FSL) a critical framework for Computer Aided Diagnostics, but we observed t

CHIMERA: A Knowledge Base of Scientific Idea Recombinations for Research Analysis and Ideation

arXiv:2505.20779v5 Announce Type: replace Abstract: A hallmark of human innovation is recombination -- the creation of novel ideas by integrating elements from existing concepts and mechanisms. In thi

Class-specific diffusion models improve military object detection in a low-data domain

arXiv:2604.18076v1 Announce Type: new Abstract: Diffusion-based image synthesis has emerged as a promising source of synthetic training data for AI-based object detection and classification. In this w

Classification of systolic murmurs in heart sounds using multiresolution complex Gabor dictionary and vision transformer

arXiv:2604.16563v1 Announce Type: new Abstract: Systolic murmurs are extra heart sounds that occur during the contraction phase of the cardiac cycle, often indicating heart abnormalities caused by tur

Clinical Note Bloat Reduction for Efficient LLM Use

arXiv:2604.16364v1 Announce Type: cross Abstract: Health systems are rapidly deploying large language models (LLMs) that use clinical notes for clinical decision support applications. However, modern

Co-generation of Layout and Shape from Text via Autoregressive 3D Diffusion

arXiv:2604.16552v1 Announce Type: new Abstract: Recent text-to-scene generation approaches largely reduced the manual efforts required to create 3D scenes. However, their focus is either to generate a

CoAct: Co-Active LLM Preference Learning with Human-AI Synergy

arXiv:2604.17501v1 Announce Type: new Abstract: Learning from preference-based feedback has become an effective approach for aligning LLMs across diverse tasks. However, high-quality human-annotated p

Coevolving Representations in Joint Image-Feature Diffusion

arXiv:2604.17492v1 Announce Type: new Abstract: Joint image-feature generative modeling has recently emerged as an effective strategy for improving diffusion training by coupling low-level VAE latents

Comparing Human and Large Language Model Interpretation of Implicit Information

arXiv:2604.17085v1 Announce Type: new Abstract: The interpretation of implicit meanings is an integral aspect of human communication. However, this framework may not transfer to interactions with Larg

Comparison Drives Preference: Reference-Aware Modeling for AI-Generated Video Quality Assessment

arXiv:2604.17074v1 Announce Type: new Abstract: The rapid advancement of generative models has led to a growing volume of AI-generated videos, making the automatic quality assessment of such videos in

Compiling OpenSCENARIO 2.1 for Scenario-Based Testing in CARLA

arXiv:2604.16452v1 Announce Type: new Abstract: While the ASAM OpenSCENARIO 2.1 Domain-Specific Language (DSL) enables declarative, intent-driven authoring for Scenario-Based Testing (SBT), its integr

Compressing then Matching: An Efficient Pre-training Paradigm for Multimodal Embedding

arXiv:2511.08480v3 Announce Type: replace Abstract: Multimodal Large Language Models advance multimodal representation learning by acquiring transferable semantic embeddings, thereby substantially enh

Conformal Prediction-Based MPC for Stochastic Linear Systems

arXiv:2512.10738v2 Announce Type: replace-cross Abstract: We propose a stochastic model predictive control (MPC) framework for linear systems subject to joint-in-time chance constraints under unknown

ConforNets: Latents-Based Conformational Control in OpenFold3

arXiv:2604.18559v1 Announce Type: cross Abstract: Models from the AlphaFold (AF) family reliably predict one dominant conformation for most well-ordered proteins but struggle to capture biologically r

Conservative Judge J. Michael Luttig is warning that Trump is already preparing to rig the 2026 midterms, not by one single scheme but by a …

Conservative Judge J. Michael Luttig is warning that Trump is already preparing to rig the 2026 midterms, not by one single scheme but by a whole “buffet of options” to throw the election into chaos.

researchyann-lecun--x

Context Matters: Peer-Aware Student Behavioral Engagement Measurement via VLM Action Parsing and LLM Sequence Classification

arXiv:2601.06394v3 Announce Type: replace Abstract: Understanding student behavior in the classroom is essential to improve both pedagogical quality and student engagement. Existing methods for predic

Continuous ageing trajectory representations for knee-aware lifetime prediction of lithium-ion batteries across heterogeneous dataset

arXiv:2604.16580v1 Announce Type: new Abstract: Accurate assessment of lithium-ion battery ageing is challenged by cell-to-cell variability, heterogeneous cycling protocols, and limited transferabilit

Continuous Focus Groups: A Longitudinal Method for Clinical HRI in Autism Care

arXiv:2604.18197v1 Announce Type: cross Abstract: Qualitative methods are important to use alongside quantitative methods to improve Human-Robot Interaction (HRI), yet they are often applied in static

Contrastive Attribution in the Wild: An Interpretability Analysis of LLM Failures on Realistic Benchmarks

arXiv:2604.17761v1 Announce Type: cross Abstract: Interpretability tools are increasingly used to analyze failures of Large Language Models (LLMs), yet prior work largely focuses on short prompts or t

Convergence theory for Hermite approximations under adaptive coordinate transformations

arXiv:2604.16975v1 Announce Type: cross Abstract: Recent work has shown that parameterizing and optimizing coordinate transformations using normalizing flows, i.e., invertible neural networks, can sig

Countdown-Code: A Testbed for Studying The Emergence and Generalization of Reward Hacking in RLVR

arXiv:2603.07084v2 Announce Type: replace-cross Abstract: Reward hacking is a form of misalignment in which models overoptimize proxy rewards without genuinely solving the underlying task. Precisely m

CSF: Black-box Fingerprinting via Compositional Semantics for Text-to-Image Models

arXiv:2604.16363v1 Announce Type: cross Abstract: Text-to-image models are commercially valuable assets often distributed under restrictive licenses, but such licenses are enforceable only when violat

Culinary Crossroads: A RAG Framework for Enhancing Diversity in Cross-Cultural Recipe Adaptation

arXiv:2507.21934v2 Announce Type: replace Abstract: In cross-cultural recipe adaptation, the goal is not only to ensure cultural appropriateness and retain the original dish's essence, but also to pro

CWT-Enhanced Vibration Sensing With Spatial Fault Localization Using YOLO

arXiv:2509.03070v4 Announce Type: replace-cross Abstract: This letter presents a CWT-enhanced vibration sensing framework for bearing fault monitoring through spatial localization on time-frequency sp

D-Prism: Differentiable Primitives for Structured Dynamic Modeling

arXiv:2604.17082v1 Announce Type: new Abstract: Capturing both geometry and rigid motion for structured dynamic objects, like multi-part assemblies or jointed mechanisms, remains a key challenge. Exis

DARLING: Detection Augmented Reinforcement Learning with Non-Stationary Guarantees

arXiv:2604.16684v1 Announce Type: new Abstract: We study model-free reinforcement learning (RL) in non-stationary finite-horizon episodic Markov decision processes (MDPs) without prior knowledge of th

DART: Learning-Enhanced Model Predictive Control for Dual-Arm Non-Prehensile Manipulation

arXiv:2604.17833v1 Announce Type: new Abstract: What appears effortless to a human waiter remains a major challenge for robots. Manipulating objects nonprehensilely on a tray is inherently difficult,

Data Compressibility Quantifies LLM Memorization

arXiv:2507.06056v4 Announce Type: replace Abstract: Large Language Models (LLMs) are known to memorize portions of their training data, sometimes even reproduce content verbatim when prompted appropri

Data Mixing for Large Language Models Pretraining: A Survey and Outlook

arXiv:2604.16380v1 Announce Type: new Abstract: Large language models (LLMs) rely on pretraining on massive and heterogeneous corpora, where training data composition has a decisive impact on training

Decisive: Guiding User Decisions with Optimal Preference Elicitation from Unstructured Documents

arXiv:2604.18122v1 Announce Type: new Abstract: Decision-making is a cognitively intensive task that requires synthesizing relevant information from multiple unstructured sources, weighing competing f