research

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

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

DGX agent

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

researcharxiv-cs-ai

15 Apr 2026

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

LLMs Struggle with Abstract Meaning Comprehension More Than Expected

arXiv:2604.12018v1 Announce Type: cross Abstract: Understanding abstract meanings is crucial for advanced language comprehension. Despite extensive research, abstract words remain challenging due to t

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

Loss-Driven Bayesian Active Learning

arXiv:2604.11995v1 Announce Type: new Abstract: The central goal of active learning is to gather data that maximises downstream predictive performance, but popular approaches have limited flexibility

Lyra 2.0: Explorable Generative 3D Worlds

arXiv:2604.13036v1 Announce Type: new Abstract: Recent advances in video generation enable a new paradigm for 3D scene creation: generating camera-controlled videos that simulate scene walkthroughs, t

Machine Learning-Based Real-Time Detection of Compensatory Trunk Movements Using Trunk-Wrist Inertial Measurement Units

arXiv:2604.12591v1 Announce Type: new Abstract: Compensatory trunk movements (CTMs) are commonly observed after stroke and can lead to maladaptive movement patterns, limiting targeted training of affe

researcharxiv-cs-ro

Machine learning for four-dimensional SU(3) lattice gauge theories

arXiv:2604.12416v1 Announce Type: cross Abstract: In this review I summarize how machine learning can be used in lattice gauge theory simulations and what ap-proaches are currently available to improv

MAML-KT: Addressing Cold Start Problem in Knowledge Tracing for New Students via Few-Shot Model-Agnostic Meta Learning

arXiv:2603.00137v2 Announce Type: replace-cross Abstract: Knowledge tracing (KT) models are commonly evaluated by training on early interactions from all students and testing on later responses. While

MAST: Mask-Guided Attention Mass Allocation for Training-Free Multi-Style Transfer

arXiv:2604.12281v1 Announce Type: cross Abstract: Style transfer aims to render a content image with the visual characteristics of a reference style while preserving its underlying semantic layout and

metasnf: Meta Clustering with Similarity Network Fusion in R

arXiv:2410.17976v2 Announce Type: replace-cross Abstract: metasnf is an R package that enables users to apply meta clustering, a method for efficiently searching a broad space of cluster solutions by

MetFuse: Figurative Fusion between Metonymy and Metaphor

arXiv:2604.12919v1 Announce Type: new Abstract: Metonymy and metaphor often co-occur in natural language, yet computational work has studied them largely in isolation. We introduce a framework that tr

Mid-training is essential for LLM reasoning, IBM study shows

IBM Research has demonstrated that mid-training — a dedicated training phase between initial pre-training and fine-tuning — is essential for improving reasoning capabilities in large language models (

researchibm-research

Mixed-Integer vs. Continuous Model Predictive Control for Binary Thrusters: A Comparative Study

arXiv:2603.19796v3 Announce Type: replace-cross Abstract: Binary on/off thrusters are commonly used for spacecraft attitude and position control during proximity operations. However, their discrete na

researcharxiv-cs-ro

MultiDocFusion: Hierarchical and Multimodal Chunking Pipeline for Enhanced RAG on Long Industrial Documents

arXiv:2604.12352v1 Announce Type: new Abstract: RAG-based QA has emerged as a powerful method for processing long industrial documents. However, conventional text chunking approaches often neglect com

Multilingual Multi-Label Emotion Classification at Scale with Synthetic Data

arXiv:2604.12633v1 Announce Type: new Abstract: Emotion classification in multilingual settings remains constrained by the scarcity of annotated data: existing corpora are predominantly English, singl

My bets on open models, mid-2026

A mid-2026 outlook piece from the Interconnects AI newsletter in which the author makes specific predictions about the trajectory of open-weight language models, likely covering expected capability mi

researchinterconnects

[N] AMA Reminder: Max Welling

researchr-machinelearning

This Reddit post is a reminder to the r/MachineLearning community about an upcoming Ask Me Anything (AMA) session with Max Welling, Chief AI Officer at CuspAI and Professor of Machine Learning at the

Navigating the Accuracy-Size Trade-Off with Flexible Model Merging

arXiv:2505.23209v3 Announce Type: replace Abstract: Model merging has emerged as an efficient method to combine multiple single-task fine-tuned models. The merged model can enjoy multi-task capabiliti

Neural Dynamic GI: Random-Access Neural Compression for Temporal Lightmaps in Dynamic Lighting Environments

arXiv:2604.12625v1 Announce Type: cross Abstract: High-quality global illumination (GI) in real-time rendering is commonly achieved using precomputed lighting techniques, with lightmap as the standard

No one’s sure if synthetic mirror life will kill us all

For four days in February 2019, some 30 synthetic biologists and ethicists hunkered down at a conference center in Northern Virginia to brainstorm high-risk, cutting-edge, irresistibly exciting ideas

researchmit-tech-review

@NousResearch Creative Director is working overtime 😁

Nous Research's Creative Director appears to be putting in significant effort on a project or initiative, as highlighted in a lighthearted post from the organization's X (formerly Twitter) account. Th

researchnous-research--x

OmniFood8K: Single-Image Nutrition Estimation via Hierarchical Frequency-Aligned Fusion

arXiv:2604.12356v1 Announce Type: new Abstract: Accurate estimation of food nutrition plays a vital role in promoting healthy dietary habits and personalized diet management. Most existing food datase

On the Convergence Analysis of Muon

arXiv:2505.23737v2 Announce Type: replace-cross Abstract: The majority of parameters in neural networks are naturally represented as matrices. However, most commonly used optimizers treat these matrix

On the Mathematical Relationship Between Layer Normalization and Dynamic Activation Functions

arXiv:2503.21708v4 Announce Type: replace-cross Abstract: Layer normalization (LN) is an essential component of modern neural networks. While many alternative techniques have been proposed, none of th

One of the fastest ways to lose trust in a self-hosted LLM: prompt injection compliance [P]

researchr-machinelearning

This r/MachineLearning post discusses how self-hosted LLMs that comply with prompt injection attempts — effectively following malicious or overriding instructions embedded in user input — represent a

One Token Away from Collapse: The Fragility of Instruction-Tuned Helpfulness

arXiv:2604.13006v1 Announce Type: cross Abstract: Instruction-tuned large language models produce helpful, structured responses, but how robust is this helpfulness when trivially constrained? We show

One View Is Enough! Monocular Training for In-the-Wild Novel View Generation

arXiv:2603.23488v2 Announce Type: replace Abstract: Monocular novel-view synthesis has long required multi-view image pairs for supervision, limiting training data scale and diversity. We argue it is

OpenTME: An Open Dataset of AI-powered H&E Tumor Microenvironment Profiles from TCGA

arXiv:2604.12075v1 Announce Type: cross Abstract: The tumor microenvironment (TME) plays a central role in cancer progression, treatment response, and patient outcomes, yet large-scale, consistent, an

OSC: Hardware Efficient W4A4 Quantization via Outlier Separation in Channel Dimension

arXiv:2604.12782v1 Announce Type: cross Abstract: While 4-bit quantization is essential for high-throughput deployment of Large Language Models, activation outliers often lead to significant accuracy

[P] Added 8 Indian languages to Chatterbox TTS via LoRA — 1.4% of parameters, no phoneme engineering [P]

researchr-machinelearning

A community researcher shared on r/MachineLearning how they extended Chatterbox TTS — Resemble AI's open-source, 500M-parameter model — to support 8 Indian languages using LoRA (Low-Rank Adaptation),

PianoFlow: Music-Aware Streaming Piano Motion Generation with Bimanual Coordination

arXiv:2604.12856v1 Announce Type: new Abstract: Audio-driven bimanual piano motion generation requires precise modeling of complex musical structures and dynamic cross-hand coordination. However, exis

Pictorial and apictorial polygonal jigsaw puzzles from arbitrary number of crossing cuts

arXiv:2008.07644v3 Announce Type: replace-cross Abstract: Jigsaw puzzle solving, the problem of constructing a coherent whole from a set of non-overlapping unordered visual fragments, is fundamental t

PILOT: Planning via Internalized Latent Optimization Trajectories for Large Language Models

arXiv:2601.19917v2 Announce Type: replace Abstract: Strategic planning is critical for multi-step reasoning, yet compact Large Language Models (LLMs) often lack the capacity to formulate global strate

Point Prompting: Counterfactual Tracking with Video Diffusion Models

arXiv:2510.11715v2 Announce Type: replace Abstract: Trackers and video generators solve closely related problems: the former analyze motion, while the latter synthesize it. We show that this connectio

Privacy-Preserving Structureless Visual Localization via Image Obfuscation

arXiv:2604.12068v1 Announce Type: new Abstract: Visual localization is the task of estimating the camera pose of an image relative to a scene representation. In practice, visual localization systems a

Privacy-Preserving Transfer Learning for Community Detection using Locally Distributed Multiple Networks

arXiv:2504.00890v2 Announce Type: replace-cross Abstract: Modern applications increasingly involve highly sensitive network data, where raw edges cannot be shared due to privacy constraints. We propos

PrivEraserVerify: Efficient, Private, and Verifiable Federated Unlearning

arXiv:2604.12348v1 Announce Type: new Abstract: Federated learning (FL) enables collaborative model training without sharing raw data, offering a promising path toward privacy preserving artificial in

Prompt Evolution for Generative AI: A Classifier-Guided Approach

arXiv:2305.16347v2 Announce Type: replace-cross Abstract: Synthesis of digital artifacts conditioned on user prompts has become an important paradigm facilitating an explosion of use cases with genera

QMC-Net: Data-Aware Quantum Representations for Remote Sensing Image Classification

arXiv:2604.11817v1 Announce Type: cross Abstract: Hybrid quantum-classical models offer a promising route for learning from complex data; however, their application to multi-band remote sensing imager

Quantifying Cross-Modal Interactions in Multimodal Glioma Survival Prediction via InterSHAP: Evidence for Additive Signal Integration

arXiv:2603.29977v2 Announce Type: replace-cross Abstract: Multimodal deep learning for cancer prognosis is commonly assumed to benefit from synergistic cross-modal interactions, yet this assumption ha