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Improving Lexical Difficulty Prediction with Context-Aligned Contrastive Learning and Ridge Ensembling

arXiv:2605.08950v1 Announce Type: cross Abstract: Lexical difficulty prediction is a fundamental problem in language learning and readability assessment, requiring models to estimate word difficulty a

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Research

Improving Temporal Action Segmentation via Constraint-Aware Decoding

DGX agent

arXiv:2605.10149v1 Announce Type: new Abstract: Temporal action segmentation (TAS) divides untrimmed videos into labeled action segments. While fully supervised methods have advanced the field, challe

researcharxiv-cs-cv

12 May 2026

Improving Text-to-Image Generation with Intrinsic Self-Confidence Rewards

arXiv:2603.00918v3 Announce Type: replace-cross Abstract: Text-to-image generation powers content creation across design, media, and data augmentation. Post-training of text-to-image generative models

Improving TMS EEG Signal Quality for Closed-Loop Neuro Stimulation via Source-Domain Denoising

arXiv:2605.08184v1 Announce Type: cross Abstract: This research addresses a validated TMS EEG cleaning pipeline and a corresponding benchmark dataset. It evaluates two widely used artifact removal pip

'In California, every professor has 10 different startups with their students. In some Canadian universities, it's one professor out of ten.…

'In California, every professor has 10 different startups with their students. In some Canadian universities, it's one professor out of ten.' @jpineau1, Chief AI Officer at @Cohere at #WebSummitVancou

model-releasescohere--x

In-Context Fixation: When Demonstrated Labels Override Semantics in Few-Shot Classification

arXiv:2605.08295v1 Announce Type: cross Abstract: While random demonstration labels barely hurt in-context learning (Min et al., 2022), we show that homogeneous labels--even semantically valid ones--c

In KAME, a fast speech model starts replying instantly, while a backend LLM runs in parallel to inject deep knowledge on the fly. It’s a com…

In KAME, a fast speech model starts replying instantly, while a backend LLM runs in parallel to inject deep knowledge on the fly. It’s a completely different way to approach conversational AI, making

researchdavid-ha--x

Incorporating rank-free coupling and external field via an incoherent modulated spatial photonic Ising machine

arXiv:2512.21587v2 Announce Type: replace-cross Abstract: Spatial photonic Ising machines offer a novel optical platform for optimization and spin-model simulation, but existing diffraction-based sche

researcharxiv-cs-lg

Increasing the Efficiency of DETR for Maritime High-Resolution Images

arXiv:2605.10269v1 Announce Type: new Abstract: Maritime object detection is critical for the safe navigation of unmanned surface vessels (USVs), requiring accurate recognition of obstacles from small

researcharxiv-cs-cv

Incremental Multilingual Text2Cypher with Adapter Combination

model-releasesarxiv-cs-cl

arXiv:2601.16097v2 Announce Type: replace Abstract: Large Language Models enable users to access database using natural language interfaces using tools like Text2SQL, Text2SPARQL, and Text2Cypher, whi

Tutorials

Inductive Entity Representations from Text via Link Prediction

arXiv:2010.03496v4 Announce Type: replace-cross Abstract: Knowledge Graphs (KG) are of vital importance for multiple applications on the web, including information retrieval, recommender systems, and

tutorialsarxiv-cs-ai

IndustryBench: Probing the Industrial Knowledge Boundaries of LLMs

arXiv:2605.10267v1 Announce Type: new Abstract: In industrial procurement, an LLM answer is useful only if it survives a standards check: recommended material must match operating condition, every par

INFANiTE: Implicit Neural representation for high-resolution Fetal brain spatio-temporal Atlas learNing from clinical Thick-slicE MRI

arXiv:2605.09977v1 Announce Type: new Abstract: Spatio-temporal fetal brain atlases are important for characterizing normative neurodevelopment and identifying congenital anomalies. However, existing

researcharxiv-cs-cv

Infinite Mask Diffusion for Few-Step Distillation

arXiv:2605.10518v1 Announce Type: cross Abstract: Masked Diffusion Models (MDMs) have emerged as a promising alternative to autoregressive models in language modeling, offering the advantages of paral

Applications

Information Density as a Quantitative Measure for AI-enabled Virtual Sensing: Feasibility and Limits

arXiv:2605.08180v1 Announce Type: cross Abstract: Modern IoT and sensor networks generate vast amounts of data, posing significant challenges for storage, transmission, and real-time processing. Tradi

applicationsarxiv-cs-ai

Applications

Information Filtering via Variational Regularization for Robot Manipulation

arXiv:2601.21926v4 Announce Type: replace Abstract: Diffusion-based visuomotor policies built on 3D visual representations have achieved strong performance in learning complex robotic skills. However,

applicationsarxiv-cs-ro

Agents

Informative Path Planning with Guaranteed Estimation Uncertainty

arXiv:2602.05198v2 Announce Type: replace Abstract: Environmental monitoring robots often need to estimate data fields (e.g., salinity, temperature, bathymetry) under tight resource constraints. Class

agentsarxiv-cs-ro

Initiation of Interaction Detection Framework using a Nonverbal Cue for Human-Robot Interaction

arXiv:2605.10087v1 Announce Type: new Abstract: This paper describes an initiation of interaction(IoI) detection framework without keywords for human-robot interaction(HRI) based on audio and vision s

local-aiarxiv-cs-cv

Inpainting physics: self-supervised learning for context-driven fluid simulation

arXiv:2605.08832v1 Announce Type: new Abstract: Neural surrogate models for computational fluid dynamics (CFD) are typically trained as forward operators that map explicit problem specifications, such

local-aiarxiv-cs-lg

Agents

Insider Attacks in Multi-Agent LLM Consensus Systems

arXiv:2605.08268v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed in multi-agent systems where agents communicate in natural language to solve tasks jointly. A k

agentsarxiv-cs-ai

Insight: Enhancing Mobile Accessibility for Blind and Visually Impaired Users with LLMs

arXiv:2605.09803v1 Announce Type: cross Abstract: This research paper addresses the limitations of current mobile accessibility services like TalkBack, which provide manual gesture-based sequential fe

Instance-Adaptive Online Multicalibration

arXiv:2605.09273v1 Announce Type: new Abstract: We study online multicalibration beyond the worst-case. We give a single, efficient algorithm which dynamically interpolates between benign and worst-ca

researcharxiv-cs-lg

Instruction Adherence in Coding Agent Configuration Files: A Factorial Study of Four File-Structure Variables

model-releasesarxiv-cs-cl

arXiv:2605.10039v1 Announce Type: cross Abstract: Frontier coding agents read configuration files (CLAUDE.md, AGENTS.md, Cursor Rules) at session start and are expected to follow the conventions insid

Instruction Anchor: Dissecting the Mechanistic Dynamics of Modality Arbitration

arXiv:2602.03677v2 Announce Type: replace Abstract: Modality following is the ability to selectively leverage multimodal contexts based on user instructions. It is fundamental to the safety and reliab

safetyarxiv-cs-cl

Industry

Instructure reached a deal with hackers who breached its Canvas platform to return stolen data and destroy copies, without disclosing what it gave in exchange (Qasim Nauman/New York Times)

Qasim Nauman / New York Times: Instructure reached a deal with hackers who breached its Canvas platform to return stolen data and destroy copies, without disclosing what it gave in exchange — Instruct

industrytechmeme

Integrated Hierarchical Decision-Making in Inverse Kinematic Planning and Control

arXiv:2412.01324v4 Announce Type: replace Abstract: This work presents a novel and efficient nonlinear programming framework that tightly integrates hierarchical decision-making with whole-body invers

researcharxiv-cs-ro

Intelligent Autonomous Orchestration for Distributed Cloud Resources using Complex-Stability Analysis

arXiv:2605.08139v1 Announce Type: cross Abstract: In modern distributed cloud environments, efficient resource allocation is required as traditional scaling mechanisms are often subject to cloud thras

Tutorials

Interactive Benchmarks

arXiv:2603.04737v2 Announce Type: replace Abstract: Existing reasoning evaluation paradigms suffer from different limitations: fixed benchmarks are increasingly saturated and vulnerable to contaminati

tutorialsarxiv-cs-ai

Interactive Critique-Revision Training for Reliable Structured LLM Generation

arXiv:2605.08327v1 Announce Type: cross Abstract: In structured decision-making workflows such as form filling, compliance checking, and maintenance reporting, LLM outputs must be locally correct, glo

local-aiarxiv-cs-ai

Interactive Inverse Reinforcement Learning of Interaction Scenarios via Bi-level Optimization

arXiv:2605.08131v1 Announce Type: new Abstract: Inverse reinforcement learning (IRL) learns a reward function and a corresponding policy that best fit the demonstration data of an expert. However, in

safetyarxiv-cs-lg

Industry

Internal emails: xAI added 19 gas turbines to Colossus 2 over the past two months; xAI is fighting a lawsuit alleging Clean Air Act violations at the site (Molly Taft/Wired)

Molly Taft / Wired: Internal emails: xAI added 19 gas turbines to Colossus 2 over the past two months; xAI is fighting a lawsuit alleging Clean Air Act violations at the site — Emails show that Elon M

industrytechmeme

Agents

Internal vs. External: Comparing Deliberation and Evolution for Multi-Agent Constitutional Design

arXiv:2605.09128v1 Announce Type: cross Abstract: Multi-agent AI systems need behavioral constitutions, but it is unresolved whether such rules should emerge internally through agent self-governance o

agentsarxiv-cs-ai

Internalizing Safety Understanding in Large Reasoning Models via Verification

arXiv:2605.08930v1 Announce Type: new Abstract: While explicit Chain-of-Thought (CoT) empowers large reasoning models (LRMs), it enables the generation of riskier final answers. Current alignment para

Interpretable Coreference Resolution Evaluation Using Explicit Semantics

arXiv:2605.10627v1 Announce Type: cross Abstract: Coreference resolution is typically evaluated using aggregate statistical metrics such as CoNLL-F1, which measure structural overlap between predicted

Interpretable Machine Learning for Football Performance Analysis: Evidence of Limited Transferability from Elite Leagues to University Competition

arXiv:2605.10796v1 Announce Type: new Abstract: Machine learning has become increasingly prevalent in football performance analysis, yet most studies prioritize predictive accuracy while implicitly as

Intervention-Based Time Series Causal Discovery via Simulator-Generated Interventional Distributions

arXiv:2605.09870v1 Announce Type: cross Abstract: We propose SVAR-FM (Structural VAR with Flow Matching), a framework for time series causal discovery that treats a physics-based simulator as a mechan

Intrinsic Guardrails: How Semantic Geometry of Personality Interacts with Emergent Misalignment in LLMs

arXiv:2605.10633v1 Announce Type: cross Abstract: Fine-tuning Large Language Models (LLMs) on benign narrow data can sometimes induce broad harmful behaviors, a vulnerability termed emergent misalignm

Intrinsic Muon: Spectral Optimization on Riemannian Matrix Manifolds

arXiv:2605.09238v1 Announce Type: cross Abstract: Muon and related norm-constrained matrix optimizers have become central to large-scale learning problems. They are formulated as a linear maximization

Industry

Introducing Flux Matching, a generative modeling paradigm that generalizes diffusion models to vector fields that need not be the score func…

Introducing Flux Matching, a generative modeling paradigm that generalizes diffusion models to vector fields that need not be the score function. Enables structural priors in the dynamics, faster samp

industryemad-mostaque--x

Tools

Introducing voice finder — a new tool to quickly find the right voice for your app from over 600+ voices

Together AI launched Voice Finder, a tool designed to help developers quickly select appropriate voices for their applications from a library of over 600 voice options. The tool streamlines the voice

toolstogether-ai-blog

Tools

Introducing voice finder from Together AI, a new tool to search, filter, and audition 600+ voices across leading TTS models. AI natives can …

Introducing voice finder from Together AI, a new tool to search, filter, and audition 600+ voices across leading TTS models. AI natives can now find the right voice for their app faster by describing

toolstogether-ai--x

Tutorials

IntroLM: Introspective Language Models via Prefilling-Time Self-Evaluation

arXiv:2601.03511v2 Announce Type: replace-cross Abstract: A major challenge for the operation of large language models (LLMs) is how to predict whether a specific LLM will produce sufficiently high-qu

tutorialsarxiv-cs-ai

Inverse Design for Conditional Distribution Matching

arXiv:2605.09439v1 Announce Type: new Abstract: Generative models are powerful tools for sampling from a learned distribution P(Y mid X), and inverse-design methods invert this map to find an input x

researcharxiv-cs-lg

Inverse Design of Multi-Layer Sub-Pixel-Resolution RF Passives Through Grayscale Diffusion with Flexible S-Parameter Conditioning

model-releasesarxiv-cs-lg

arXiv:2605.08233v1 Announce Type: cross Abstract: Inverse design of RF passive components from S-parameters is a high-dimensional, ill-posed problem, and prior generative approaches are limited to sin

Investigating Anisotropy in Visual Grounding under Controlled Counterfactual Perturbations

arXiv:2605.09090v1 Announce Type: cross Abstract: Visual Grounding benchmarks assume that the object described by a referring expression is always present in the image, and grounding models are theref

IPAD-CLIP: Teaching CLIP to Detect Image Local Perceptual Artifacts

model-releasesarxiv-cs-cv

arXiv:2605.08664v1 Announce Type: new Abstract: Current image quality assessment methods are heavily biased towards global distortions (e.g., noise, blur), neglecting local perceptual artifacts such a

iPay: Integrated Payment Action Recognition via Multimodal Networks and Adaptive Spatial Prior Learning

arXiv:2605.10732v1 Announce Type: cross Abstract: Automated transit payment analysis is vital for scalable fare auditing and passenger analytics, yet practice still relies on limited manual inspection

local-aiarxiv-cs-ai

Is Class Signal Clustered or Routed in Task-Induced Implicit Neural Representation Weight Spaces?

arXiv:2605.08281v1 Announce Type: new Abstract: Implicit neural representations (INRs) encode images as neural-network weights, making image classification a problem of weight-space classifiability. A

safetyarxiv-cs-cv