Search: “research”

Distinct mechanisms underlying in-context learning in transformers

arXiv:2604.12151v1 Announce Type: new Abstract: Modern distributed networks, notably transformers, acquire a remarkable ability (termed `in-context learning') to adapt their computation to input stati

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Distorted or Fabricated? A Survey on Hallucination in Video LLMs

DGX agent

arXiv:2604.12944v1 Announce Type: cross Abstract: Despite significant progress in video-language modeling, hallucinations remain a persistent challenge in Video Large Language Models (Vid-LLMs), refer

researcharxiv-cs-ai

15 Apr 2026

Do Transformers Use their Depth Adaptively? Evidence from a Relational Reasoning Task

arXiv:2604.12426v1 Announce Type: cross Abstract: We investigate whether transformers use their depth adaptively across tasks of increasing difficulty. Using a controlled multi-hop relational reasonin

Does Visual Token Pruning Improve Calibration? An Empirical Study on Confidence in MLLMs

arXiv:2604.12035v1 Announce Type: new Abstract: Visual token pruning is a widely used strategy for efficient inference in multimodal large language models (MLLMs), but existing work mainly evaluates i

Dynamic Modeling and Robust Gait Optimization of a Compliant Worm Robot

arXiv:2604.12031v1 Announce Type: new Abstract: Worm-inspired robots provide an effective locomotion strategy for constrained environments by combining cyclic body deformation with alternating anchori

researcharxiv-cs-ro

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning

arXiv:2409.06679v3 Announce Type: replace Abstract: Processing long contexts is increasingly important for Large Language Models (LLMs) in tasks like multi-turn dialogues, code generation, and documen

Efficiency of Proportional Mechanisms in Online Auto-Bidding Advertising

arXiv:2604.12799v1 Announce Type: cross Abstract: The rise of automated bidding strategies in online advertising presents new challenges in designing and analyzing efficient auction mechanisms. In thi

Efficient and Scalable Granular-ball Graph Coarsening Method for Large-scale Graph Node Classification

arXiv:2603.29148v2 Announce Type: replace-cross Abstract: Graph Convolutional Network (GCN) is a model that can effectively handle graph data tasks and has been successfully applied. However, for larg

Efficient Inference for Large Vision-Language Models: Bottlenecks, Techniques, and Prospects

arXiv:2604.05546v2 Announce Type: replace Abstract: Large Vision-Language Models (LVLMs) enable sophisticated reasoning over images and videos, yet their inference is hindered by a systemic efficiency

Efficient Semantic Image Communication for Traffic Monitoring at the Edge

arXiv:2604.12622v1 Announce Type: cross Abstract: Many visual monitoring systems operate under strict communication constraints, where transmitting full-resolution images is impractical and often unne

Elastic Net Regularization and Gabor Dictionary for Classification of Heart Sound Signals using Deep Learning

arXiv:2604.12483v1 Announce Type: cross Abstract: In this article, we propose the optimization of the resolution of time-frequency atoms and the regularization of fitting models to obtain better repre

Enabling Ultra-Fast Cardiovascular Imaging Across Heterogeneous Clinical Environments with A Generalist Foundation Model and Multimodal Database

arXiv:2512.21652v2 Announce Type: replace-cross Abstract: Multimodal cardiovascular magnetic resonance (CMR) imaging provides comprehensive and non-invasive insights into cardiovascular disease (CVD)

Enhance-then-Balance Modality Collaboration for Robust Multimodal Sentiment Analysis

arXiv:2604.12518v1 Announce Type: new Abstract: Multimodal sentiment analysis (MSA) integrates heterogeneous text, audio, and visual signals to infer human emotions. While recent approaches leverage c

Enhancing Text-to-Image Diffusion Transformer via Split-Text Conditioning

arXiv:2505.19261v2 Announce Type: replace-cross Abstract: Current text-to-image diffusion generation typically employs complete-text conditioning. Due to the intricate syntax, diffusion transformers (

Exploring Concept Subspace for Self-explainable Text-Attributed Graph Learning

arXiv:2604.11986v1 Announce Type: new Abstract: We introduce Graph Concept Bottleneck (GCB) as a new paradigm for self-explainable text-attributed graph learning. GCB maps graphs into a subspace, conc

Fall Risk and Gait Analysis in Community-Dwelling Older Adults using World-Spaced 3D Human Mesh Recovery

arXiv:2604.11961v1 Announce Type: new Abstract: Gait assessment is a key clinical indicator of fall risk and overall health in older adults. However, standard clinical practice is largely limited to s

Free Random Projection for In-Context Reinforcement Learning

arXiv:2504.06983v3 Announce Type: replace Abstract: Hierarchical inductive biases are hypothesized to promote generalizable policies in reinforcement learning, as demonstrated by explicit hyperbolic l

From Attenuation to Attention: Variational Information Flow Manipulation for Fine-Grained Visual Perception

arXiv:2604.12508v1 Announce Type: new Abstract: While Multimodal Large Language Models (MLLMs) have demonstrated impressive capabilities in general visual understanding, they frequently falter in fine

From edges to meaning: Semantic line sketches as a cognitive scaffold for ancient pictograph invention

arXiv:2604.12865v1 Announce Type: new Abstract: Humans readily recognize objects from sparse line drawings, a capacity that appears early in development and persists across cultures, suggesting neural

From Kinematics to Dynamics: Learning to Refine Hybrid Plans for Physically Feasible Execution

arXiv:2604.12474v1 Announce Type: cross Abstract: In many robotic tasks, agents must traverse a sequence of spatial regions to complete a mission. Such problems are inherently mixed discrete-continuou

Gaussian Equivalence for Self-Attention: Asymptotic Spectral Analysis of Attention Matrix

arXiv:2510.06685v2 Announce Type: replace-cross Abstract: Self-attention layers have become fundamental building blocks of modern deep neural networks, yet their theoretical understanding remains limi

Generative Modeling Enables Molecular Structure Retrieval from Coulomb Explosion Imaging

arXiv:2511.00179v2 Announce Type: replace-cross Abstract: Capturing the structural changes that molecules undergo during chemical reactions in real space and time is a long-standing dream and an essen

GeoPl@ntNet: A Platform for Exploring Essential Biodiversity Variables

arXiv:2511.13790v2 Announce Type: replace-cross Abstract: This paper describes GeoPl@ntNet, an interactive web application designed to make Essential Biodiversity Variables accessible and understandab

Hey Republicans; He pardoned 1,600 violent criminals. You said nothing. He bulldozed the East Wing. You’ve said nothing. He’s interfered wit…

Hey Republicans; He pardoned 1,600 violent criminals. You said nothing. He bulldozed the East Wing. You’ve said nothing. He’s interfered with the release of the Epstein files. You’ve said nothing. He

researchyann-lecun--x

HiFiNet: Hierarchical Fault Identification in Wireless Sensor Networks via Edge-Based Classification and Graph Aggregation

arXiv:2511.17537v2 Announce Type: replace-cross Abstract: Wireless Sensor Networks (WSN) are the backbone of essential monitoring applications, but their deployment in unfavourable conditions increase

Hosting Live session for sub 10ms retrieval by Moss (YC backed) [N]

researchr-machinelearning

Moss is a YC-backed high-performance runtime for real-time semantic search that delivers sub-10ms lookups, instant index updates, and zero infrastructure overhead, running where the agent lives — clou

HTDC: Hesitation-Triggered Differential Calibration for Mitigating Hallucination in Large Vision-Language Models

arXiv:2604.12115v1 Announce Type: new Abstract: Large vision-language models (LVLMs) achieve strong multimodal performance, but still suffer from hallucinations caused by unstable visual grounding and

Human-Inspired Context-Selective Multimodal Memory for Social Robots

arXiv:2604.12081v1 Announce Type: new Abstract: Memory is fundamental to social interaction, enabling humans to recall meaningful past experiences and adapt their behavior accordingly based on the con

Hypergraph-State Collaborative Reasoning for Multi-Object Tracking

arXiv:2604.12665v1 Announce Type: new Abstract: Motion reasoning serves as the cornerstone of multi-object tracking (MOT), as it enables consistent association of targets across frames. However, exist

If current cuts to the Federal Science Budget proposed by the White House are approved by Congress, that will far-and-away be the largest cu…

If current cuts to the Federal Science Budget proposed by the White House are approved by Congress, that will far-and-away be the largest cut to science since the United States began funding it. Repub

researchyann-lecun--x

IMU: Influence-guided Machine Unlearning

arXiv:2508.01620v3 Announce Type: replace-cross Abstract: Machine Unlearning (MU) aims to selectively erase the influence of specific data points from pretrained models. However, most existing MU meth

Information-Theoretic Optimization for Task-Adapted Compressed Sensing Magnetic Resonance Imaging

arXiv:2604.12709v1 Announce Type: cross Abstract: Task-adapted compressed sensing magnetic resonance imaging (CS-MRI) is emerging to address the specific demands of downstream clinical tasks with sign

Agents

Inside VAKRA: Reasoning, Tool Use, and Failure Modes of Agents

VAKRA (Versatile Agent and Knowledge Reasoning Assessment) is a benchmark developed by IBM Research to evaluate AI agents on complex reasoning, tool use, and multi-step task execution across diverse d

agentshugging-face

Interpretable DNA Sequence Classification via Dynamic Feature Generation in Decision Trees

arXiv:2604.12060v1 Announce Type: cross Abstract: The analysis of DNA sequences has become critical in numerous fields, from evolutionary biology to understanding gene regulation and disease mechanism

Is Sliding Window All You Need? An Open Framework for Long-Sequence Recommendation

arXiv:2604.12372v1 Announce Type: new Abstract: Long interaction histories are central to modern recommender systems, yet training with long sequences is often dismissed as impractical under realistic

Hardware

ISSCC 2026: NVIDIA & Broadcom CPO, HBM4 & LPDDR6, TSMC Active LSI, Logic-Based SRAM, UCIe-S and More

ISSCC 2026 previews cutting-edge semiconductor research and industry presentations covering co-packaged optics (CPO) developments from NVIDIA and Broadcom, next-generation memory standards including H

hardwaresemianalysis

Jailbreaks as social engineering: 5 case studies suggest LLMs inherit human psychological vulnerabilities from training data [D]

researchr-machinelearning

This r/MachineLearning discussion post examines LLM jailbreaks through the lens of social engineering, arguing that the psychological vulnerabilities found in LLMs are not random artifacts but structu

JanusCoder: Towards a Foundational Visual-Programmatic Interface for Code Intelligence

arXiv:2510.23538v2 Announce Type: replace Abstract: The scope of neural code intelligence is rapidly expanding beyond text-based source code to encompass the rich visual outputs that programs generate

Joint Multi-Target Detection-Tracking in Cognitive Massive MIMO Radar via POMCP

arXiv:2507.17506v3 Announce Type: replace-cross Abstract: This work presents a cognitive radar (CR) framework to enhance remote sensing performance, specifically focusing on tracking multiple targets

KG-Reasoner: A Reinforced Model for End-to-End Multi-Hop Knowledge Graph Reasoning

arXiv:2604.12487v1 Announce Type: cross Abstract: Large Language Models (LLMs) exhibit strong abilities in natural language understanding and generation, yet they struggle with knowledge-intensive rea

Latent-Condensed Transformer for Efficient Long Context Modeling

arXiv:2604.12452v1 Announce Type: new Abstract: Large language models (LLMs) face significant challenges in processing long contexts due to the linear growth of the key-value (KV) cache and quadratic

Latent patterns of urban mixing in mobility analysis across five global cities

arXiv:2604.12202v1 Announce Type: new Abstract: This study leverages large-scale travel surveys for over 200,000 residents across Boston, Chicago, Hong Kong, London, and Sao Paulo. With rich individua

Learned Incremental Nonlinear Dynamic Inversion for Quadrotors with and without Slung Payloads

arXiv:2503.09441v2 Announce Type: replace Abstract: The increasing complexity of multirotor applications demands flight controllers that can accurately account for all forces acting on the vehicle. Co

researcharxiv-cs-ro

Learning Chain Of Thoughts Prompts for Predicting Entities, Relations, and even Literals on Knowledge Graphs

arXiv:2604.12651v1 Announce Type: cross Abstract: Knowledge graph embedding (KGE) models perform well on link prediction but struggle with unseen entities, relations, and especially literals, limiting

Learning to accelerate distributed ADMM using graph neural networks

arXiv:2509.05288v2 Announce Type: replace Abstract: Distributed optimization is fundamental to large-scale machine learning and control applications. Among existing methods, the alternating direction

LLM as Attention-Informed NTM and Topic Modeling as long-input Generation: Interpretability and long-Context Capability

arXiv:2510.03174v2 Announce Type: replace-cross Abstract: Topic modeling aims to produce interpretable topic representations and topic--document correspondences from corpora, but classical neural topi

Loop Corrections to the Training and Generalization Errors of Random Feature Models

arXiv:2604.12827v1 Announce Type: cross Abstract: We investigate random feature models in which neural networks sampled from a prescribed initialization ensemble are frozen and used as random features

LoSA: Locality Aware Sparse Attention for Block-Wise Diffusion Language Models

arXiv:2604.12056v1 Announce Type: new Abstract: Block-wise diffusion language models (DLMs) generate multiple tokens in any order, offering a promising alternative to the autoregressive decoding pipel