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SWE-IF: Aligning Code Evaluation with Human Preference

arXiv:2510.07315v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have catalyzed vibe coding, where users leverage LLMs to generate and iteratively refine code through natural lan

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Synthetic Benchmarks Overstate Forward-Forward Scaling: Real-Data Limits of Layer-Local Training

DGX agent

arXiv:2606.06539v1 Announce Type: cross Abstract: Forward-Forward (FF) learning [Hinton, 2022] replaces backpropagation with strictly layer-local goodness updates. Recent FF-CNN work has narrowed the

researcharxiv-cs-ai

8 Jun 2026

T2LM: Long-Term 3D Human Motion Generation from Multiple Sentences

arXiv:2406.00636v2 Announce Type: replace Abstract: In this paper, we address the challenging problem of long-term 3D human motion generation. Specifically, we aim to generate a long sequence of smoot

TA-RAG: Tone-Aware Retrieval-Augmented Generation for Peer-Support Health Communication

arXiv:2606.06794v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) successfully grounds large language model (LLM) outputs in trusted documents, but factual grounding alone is insuff

TabSwift: An Efficient Tabular Foundation Model with Row-Wise Attention

arXiv:2606.07345v1 Announce Type: new Abstract: Tabular foundation models, exemplified by TabPFN, perform prediction via in-context learning, inferring test labels directly from labeled training examp

Telling stories, making Hanzi: AI-assisted co-creation with elderly migrants in urban China

arXiv:2507.01548v3 Announce Type: replace-cross Abstract: This paper explores how older migrants in urban China can record stories that everyday language and design often miss. We ran two co-creation

Terastal: Layer-Variant-based Scheduling for Real-Time Multi-DNN Workloads on Heterogeneous Accelerators

arXiv:2606.06818v1 Announce Type: cross Abstract: Heterogeneous DNN accelerators improve soft real-time multi-DNN execution by mapping each layer to its preferred accelerator to reduce latency. Howeve

The Download: how the World Cup ball will fly and OpenAI’s “super app”

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. Why this year’s World Cup ball may not fly as far Much is new

researchmit-tech-review

The Dual Mechanisms of Spatial Variable Binding in Vision-Language Models

arXiv:2603.22278v2 Announce Type: replace Abstract: Many multimodal tasks, such as image captioning and visual question answering, require vision-language models (VLMs) to bind objects with their prop

The Effect of Training Task Diversity on In-Context Learning through the Lens of Low-Dimensional Subspaces

arXiv:2606.06814v1 Announce Type: cross Abstract: The transformer's emergent ability to perform in-context learning (ICL) has sparked a wide range of studies designed to understand its underlying mech

The Geometry of Last-Layer Model Stealing

arXiv:2606.06854v1 Announce Type: new Abstract: This paper uses geometry to explain how a machine learning model can be stolen using an already existing well-known method. The author has shown the exa

The Identity Trap in EEG Foundation Models: A Diagnostic Audit

arXiv:2606.06647v1 Announce Type: new Abstract: Objective. EEG foundation models (FMs) report strong accuracy on clinical resting-state EEG. However, high accuracy under subject-disjoint cross-validat

The Latent Space: Foundation, Evolution, Mechanism, Ability, and Outlook

arXiv:2604.02029v2 Announce Type: replace Abstract: Latent space is rapidly emerging as a native substrate for language-based models. While modern systems are still commonly understood through explici

The Lipreading Gap: Do VSR Models Perceive Visual Speech Like Human Lipreaders?

arXiv:2606.07435v1 Announce Type: cross Abstract: Visual speech recognition (VSR) models now surpass human lipreaders on benchmarks, but do such gains establish human-like visual speech perception? To

The Necessity of Setting Temperature in LLM-as-a-Judge

arXiv:2603.28304v2 Announce Type: replace Abstract: Using large language models (LLMs) as judges for evaluating model outputs has emerged as an important paradigm for automated evaluation. However, th

The point is that you should start implementing ways to encode instructions/prompts with clear goals inside automations. Nothing new but new…

The point is that you should start implementing ways to encode instructions/prompts with clear goals inside automations. Nothing new but newer LLMs are being trained to perform for longer duration uni

researchdair-ai--x

The Proxy Benders Decomposition

arXiv:2606.07403v1 Announce Type: cross Abstract: Benders decomposition is a fundamental framework for solving large-scale mixed-integer optimization problems with complicating variables that, when fi

The Sharp Phase Transition of Tyler's M-Estimator for Robust Subspace Recovery

arXiv:2606.06782v1 Announce Type: cross Abstract: Robust Subspace Recovery (RSR) aims to identify an underlying d-dimensional subspace from a dataset heavily corrupted by outliers. Complexity-theoreti

The Utility and Complexity of in- and out-of-Distribution Machine Unlearning

arXiv:2412.09119v3 Announce Type: replace Abstract: Machine unlearning, the process of selectively removing data from trained models, is increasingly crucial for addressing privacy concerns and knowle

Three-dimensional hydro-cluttered locomotion by an undulatory robot

arXiv:2606.06829v1 Announce Type: new Abstract: Aquatic robots have expanded human access to underwater environments, yet many underwater spaces contain obstacles that can disrupt open-water locomotio

researcharxiv-cs-ro

TOPSIS-RAD: Ranking According to Desires

arXiv:2606.07253v1 Announce Type: new Abstract: Traditional TOPSIS derives its reference points -- the Positive Ideal Solution (PIS) and Negative Ideal Solution (NIS) -- from the observed alternative

Towards Efficient and Exact Forgetting Services in Pre-Trained-Model-based Continual Learning

arXiv:2505.12239v2 Announce Type: replace-cross Abstract: In Continual Learning (CL), using a Pre-Trained Model (PTM) as the feature extractor has become a popular practice. Accompanied by analytic cl

TraRA: Trajectory-level Recognition Aggregation for Video Text Spotting in Urban Surveillance

arXiv:2606.07161v1 Announce Type: new Abstract: Video Text Spotting (VTS) is essential for urban surveillance and intelligent transportation systems, enabling automated reading of street signs, vehicl

Understanding Generative Recommendation with Semantic IDs from a Model-scaling View

arXiv:2509.25522v3 Announce Type: replace Abstract: Recent advancements in generative models have allowed the emergence of a promising paradigm for recommender systems (RS), known as Generative Recomm

Unified Geometry-Guided ML-FTLE for Tracking Transient Chaos from Scalar Time Series

arXiv:2606.07385v1 Announce Type: cross Abstract: Detecting transient chaos from scalar observations without governing equations represents a fundamental challenge in nonlinear dynamics. We propose a

Universal consistency of the k-NN rule in metric spaces and Nagata dimension. III

arXiv:2512.17058v3 Announce Type: replace Abstract: We establish the last missing link allowing to describe those complete separable metric spaces X in which the k nearest neighbour classifier is univ

Unmixing ATR-{mu}FTIR spectroscopic images of cross-sections of historical oil paintings

arXiv:2603.06673v2 Announce Type: replace Abstract: Spectroscopic imaging (SI) has become central to heritage science because it enables non-invasive, spatially resolved characterisation of materials

Unregistered Spectral Image Fusion: Unmixing, Adversarial Learning, and Recoverability

arXiv:2603.21510v3 Announce Type: replace-cross Abstract: This paper addresses the fusion of a pair of spatially unregistered hyperspectral image (HSI) and multispectral image (MSI) covering roughly o

Unsupervised Learning Based Focal Stack Camera Depth Estimation

arXiv:2203.07904v3 Announce Type: replace-cross Abstract: We propose an unsupervised deep learning based method to estimate depth from focal stack camera images. On the NYU-v2 dataset, our method achi

Varifold Moment Invariants for Sustainable and Explainable Contour Feature Extraction

arXiv:2606.07333v1 Announce Type: new Abstract: We introduce Varifold Moments Invariants (VMI) as a unifying framework for many previously introduced Moment Invariants. These invariants are deeply rel

Video-Based Prediction of In-Flight Particle Characteristics in Atmospheric Plasma Spraying

arXiv:2606.07416v1 Announce Type: new Abstract: Atmospheric plasma spraying (APS) is a widely used coating process in which in-flight particle temperature and velocity strongly influence coating quali

WAV: Multi-Resolution Block Residual Routing for Deep Decoder-Only Transformers

arXiv:2606.06564v1 Announce Type: cross Abstract: Residual connections are central to training deep Transformers, but standard PreNorm residual streams aggregate sublayer updates with fixed unit weigh

When Better Codebooks Are Not Enough: Predictive Performance and Behavioral Reliability in LLM Political Event Coding

arXiv:2606.06781v1 Announce Type: new Abstract: High accuracy does not necessarily make an LLM a faithful coder. This issue matters because many social-science studies rely on expert-written codebooks

When CLIP Sees More, It Fights Back Harder: Multi-View Guided Adaptive Counterattacks for Test-Time Adversarial Robustness

arXiv:2606.06938v1 Announce Type: new Abstract: Vision-language models such as CLIP have achieved remarkable zero-shot recognition capabilities, yet their robustness against adversarial perturbations

When is 3D Worth It? A Resource-Performance Frontier for CNNs and Transformers in Lung CT

arXiv:2606.06950v1 Announce Type: cross Abstract: Three-dimensional models are widely assumed preferable for volumetric medical imaging, yet their practical value depends on whether performance gains

Where Rectified Flows Leak: Characterising Membership Signals Along the Interpolation Path

arXiv:2606.07271v1 Announce Type: cross Abstract: Understanding what generative models retain from training data remains challenging, with implications for copyright and privacy. Beyond verbatim repro

Whisper Hallucination Detection and Mitigation via Hidden Representation Steering and Sparse AutoEncoders

arXiv:2606.07473v1 Announce Type: cross Abstract: Whisper, a widely adopted ASR model, is known to suffer from hallucinations - coherent transcriptions generated for non-speech audio entirely disconne

Why this year’s World Cup ball may not fly as far

Much is new about this month’s upcoming FIFA World Cup tournament, which will be held in the US, Canada, and Mexico. It hosts more teams than ever before. It’s the first to occur in three different ho

researchmit-tech-review

Your UnEmbedding Matrix is Secretly a Feature Lens for Text Embeddings

arXiv:2606.07502v1 Announce Type: new Abstract: Large language models exhibit impressive zero-shot capabilities across a wide range of downstream tasks. However, they struggle to function as off-the-s

Zero-Shot Polygon Matching with Pre-trained Models for Pose Estimation and Polygon Cloud from Challenging Stereo

arXiv:2511.05949v2 Announce Type: replace Abstract: While stereo matching has achieved maturity for 0D point and 1D line primitives, establishing correspondences for 2D polygons remains largely unexpl

Member of Technical Staff (RSI Lab) https://sakana.ai/careers/member-of-technical-staff-rsi-lab/ If you are a visionary builder ready to mov…

Member of Technical Staff (RSI Lab) https://sakana.ai/careers/member-of-technical-staff-rsi-lab/ If you are a visionary builder ready to move to Tokyo and engineer the engine of recursive discovery, w

researchdavid-ha--x

7 Jun 2026

A Cartography of Open Collaboration in Open Source AI: Mapping Practices, Motivations, and Governance in 14 Open Large Language Model Projects

arXiv:2509.25397v2 Announce Type: replace-cross Abstract: The proliferation of open large language models (LLMs) is fostering a vibrant ecosystem in artificial intelligence (AI). However, the methods

A Framework for Measuring Appropriate Reliance on Set-Valued AI Advice

arXiv:2606.06081v1 Announce Type: new Abstract: Appropriate reliance on AI advice has become a central research theme in human-AI collaboration. Existing frameworks have focused exclusively on point p

Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission

arXiv:2606.06273v1 Announce Type: cross Abstract: Lossless pixel-level image transmission is a fundamental regime beyond semantic communications, because exact recovery requires both accurate symbol p

AIS-Based Vessel Trajectory Prediction Using Memory-Augmented Neural Networks

arXiv:2606.06311v1 Announce Type: new Abstract: Accurate vessel trajectory prediction is essential for safe and efficient maritime operations, enabling collision avoidance and supporting route optimiz

An Improved CNN-LSTM Based Intrusion Detection System for IoT Networks

arXiv:2606.05776v1 Announce Type: cross Abstract: With the rapid proliferation of IoT devices, security concerns have dramatically escalated and intrusion detection systems have become critical for pr

An interpretable and trustworthy AI framework for large-scale longitudinal structure-pain association studies using data from the Osteoarthritis Initiative (OAI)

arXiv:2606.05357v1 Announce Type: new Abstract: Purpose: To develop an interpretable and trustworthy AI framework that combines deep learning based MRI Osteoarthritis Knee Score (MOAKS) prediction wit

Answer Presence Drives RAG Rewriting Gains

arXiv:2606.05633v1 Announce Type: new Abstract: Retrieval-augmented QA pipelines often route retrieved passages through an LLM rewriter before a smaller reader, lifting F1 by tens of points on multi-h