Search: “models”

Incast-Free MoE Rate-Based Scheduling

arXiv:2607.26340v1 Announce Type: cross Abstract: Mixture of Experts (MoE) architectures have become key to large language models; however, their typical round-robin (RR) scheduling introduces signifi

Kinetic Mining in Context: Few-Shot Action Synthesis via Text-to-Motion Distillation

arXiv:2512.11654v3 Announce Type: replace Abstract: The acquisition cost for large, annotated motion datasets remains a critical bottleneck for skeletal-based Human Activity Recognition (HAR). Althoug

researcharxiv-cs-cv

30 Jul 2026

Latent-IM: Latent Interaction Management for Speech LLMs

arXiv:2607.26928v1 Announce Type: new Abstract: Classical spoken dialogue systems often separated dialogue management from response realization: a policy selected the next dialogue action, and a gener

safetyarxiv-cs-cl

LLM-Grounded Dynamic Task Planning with Hierarchical Temporal Logic for Human-Aware Multi-Robot Handover

arXiv:2602.09472v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) enable non-experts to specify open-world multi-robot tasks, but the generated plans are often kinematically infea

Making Implicit Premises Explicit in Logical Understanding of Enthymemes

arXiv:2603.06114v2 Announce Type: replace Abstract: Real-world arguments in text and dialogues are normally enthymemes (i.e. some of their premises and/or claims are implicit). Natural language proces

applicationsarxiv-cs-cl

MLVC: Multi-platform Learned Video Codec for Real-World Deployment [P]

applicationsr-machinelearning

I've always found it a little strange that AI is everywhere, but the codecs we use in practice are the traditional hand-engineered systems like h.264, h.265, av1. Alexnet started the wave of neural ne

On the robustness of noisy solutions in non-convex neural networks

arXiv:2607.27000v1 Announce Type: cross Abstract: Optimization in non-convex neural network models is strongly influenced by the geometry of the solution space: sparse, isolated, point-like clusters a

Pangram 4 Technical Report

arXiv:2607.27183v1 Announce Type: new Abstract: We present Pangram 4, the latest deep-learning-based AI-text classification model from Pangram Labs. We achieve an AUROC of 0.9916 with a false positive

researcharxiv-cs-cl

Particle-Filtering-based Latent Diffusion for Inverse Problems

arXiv:2408.13868v2 Announce Type: replace Abstract: Current strategies for solving image-based inverse problems apply latent diffusion models to perform posterior sampling.However, almost all approach

PIKS: Universal Physics-Informed Kernel Methods

arXiv:2607.27062v1 Announce Type: cross Abstract: Physics-informed machine learning incorporates physical principles --often expressed via differential operators-- into data-driven models. While physi

Quantized Kimi-K3:cloud

I’m on the $20 plan and I’m not going to pay for extra usage credits to use Kimi-K3. Could the folks at Ollama quantize the model and serve it up in the cloud? submitted by /u/EvanstonNU [link] [comme

local-air-ollama

RA-Det: Towards Universal Detection of AI-Generated Images via Robustness Asymmetry

arXiv:2603.01544v2 Announce Type: replace Abstract: Recent image generators produce photo-realistic content that undermines the reliability of downstream recognition systems. As visual appearance cues

Recover, Decode, Reguard: Guard-Agnostic Defense Amplification againstEncoded VLM Jailbreaks

arXiv:2607.26574v1 Announce Type: cross Abstract: Safety classifiers ('guards') are the dominant black-box defense for vision-language models, yet they judge an input's surface form, not its meaning:

safetyarxiv-cs-lg

Robust RPC Bundle Adjustment for Multi-Date Satellite Imagery with Season-Invariant Correspondences

arXiv:2607.26973v1 Announce Type: new Abstract: Accurate refinement of Rational Polynomial Camera (RPC) models is essential for high-quality satellite image geolocation. In ground control point (GCP)-

SeasonStereo: Robust Dense Stereo Matching for Multi-Date Satellite Imagery via Generative AI

arXiv:2607.27139v1 Announce Type: new Abstract: Accurate 3D reconstruction from satellite imagery typically relies on near-simultaneous stereo pairs, limiting its applicability to diachronic settings

SENSE: Efficient EEG-to-Text via Privacy-Preserving Semantic Retrieval

arXiv:2603.17109v2 Announce Type: replace Abstract: Decoding brain activity into natural language is a major challenge in AI with important applications in assistive communication, neurotechnology, an

local-aiarxiv-cs-lg

SG-CoT: An Ambiguity-Aware Robotic Planning Framework using Scene Graph Representations

arXiv:2603.18271v3 Announce Type: replace Abstract: Ambiguity poses a major challenge to large language models (LLMs) used as robotic planners. In this letter, we present Scene Graph-Chain-of-Thought

agentsarxiv-cs-ro

Shape-Based Inductive Bias for Glioma Grading from Tumor Contours

arXiv:2607.26090v1 Announce Type: cross Abstract: Glioma grading from tumor contours is often treated as a pixel problem even when the signal of interest is shape. We align closed contours with a func

safetyarxiv-cs-cv

Single-Beat Cuffless Blood Pressure Estimation Using Ear-PPG and ECG with a Lightweight Hybrid Learning Framework

arXiv:2607.27076v1 Announce Type: new Abstract: Continuous cuffless blood pressure (BP) monitoring remains challenging due to motion artifacts, physiological variability, and the limited robustness of

applicationsarxiv-cs-lg

SkillRise: Agentic Reinforcement Learning for Cross-Task Skill Evolution

arXiv:2607.26784v1 Announce Type: new Abstract: Large language model agents often encounter related yet distinct tasks that share reusable solution patterns. Yet standard agentic reinforcement learnin

safetyarxiv-cs-lg

// The agent is its own best speculator // Agents spend a large share of wall-clock time waiting on tool results. Speculation hides that lat…

// The agent is its own best speculator // Agents spend a large share of wall-clock time waiting on tool results. Speculation hides that latency by predicting and pre-executing the next call, but exte

safetydair-ai--x

A GAN-Based Framework for Robust Data Synthesis in Satellite Internet Observations

arXiv:2607.24790v1 Announce Type: new Abstract: Low-Earth orbit (LEO) satellite Internet has become an important infrastructure for enabling ubiquitous connectivity to align with the International Tel

applicationsarxiv-cs-ai

A note on the Hugging Face agent incident

Hugging Face reported that a recent agent intrusion used Modal’s infrastructure as a launchpad, but Modal’s sandbox isolation was not breached; the malicious code executed only within the affected cus

agentsmodal-blog

AdaKP: Online Adaptive Knowledge-Point Selection for Reasoning-Oriented Reinforcement Learning

arXiv:2607.24833v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards is a powerful paradigm for eliciting reasoning in large language models, yet it suffers from severe rewar

safetyarxiv-cs-ai

AMRD: Adaptive Multi-Teacher Relational Distillation for Lightweight Speech Emotion Recognition

arXiv:2607.25289v1 Announce Type: new Abstract: On-device speech emotion recognition (SER) is critical for real-time applications, yet large self-supervised models that excel at SER are too costly for

local-aiarxiv-cs-lg

An Embarrassingly Simple Rule-based Visiting Circulation Approach to Trip Destination Prediction

arXiv:2607.25751v1 Announce Type: new Abstract: In this paper, we propose the Rule-based Visiting Circulation (RVC) model in tackling the challenge in the IEEE Big Data Cup 2022: Trip Destination Pred

Are the High-weight Neurons the Important Ones in Image Classification Neural Networks?

arXiv:2607.25529v1 Announce Type: new Abstract: As neural network models for image classification advance, neurons play critical roles in pruning, backdoor defense, and interpretability. Yet existing

researcharxiv-cs-ai

Tutorials

Bi-Level Collaborative Learning for Few-Shot Scribble-Supervised Medical Image Segmentation

arXiv:2607.25432v1 Announce Type: new Abstract: Scribble annotations offer an efficient alternative to costly pixel-wise labeling for medical image segmentation, yet in real clinical scenarios, scribb

tutorialsarxiv-cs-cv

CAST: Game Solvers as Turn-Level Teachers for LLM Agents

arXiv:2607.25308v1 Announce Type: cross Abstract: Training large language models (LLMs) to act in long-horizon games is a promising step toward generalist decision-making, yet reinforcement learning w

safetyarxiv-cs-ai

Constrained CTC Decoding for Efficient Diacritic Restoration

arXiv:2607.18946v2 Announce Type: replace Abstract: In this work, we address diacritic restoration for Arabic speech transcripts. Most speech data are undiacritized, limiting the ability of modeling f

researcharxiv-cs-cl

Controllable LLM Reasoning via Sparse Autoencoder-Based Steering

arXiv:2601.03595v2 Announce Type: replace Abstract: Large Reasoning Models (LRMs) exhibit human-like cognitive reasoning strategies (eg backtracking, cross-verification) during the reasoning process,

Cyber-Capable AI Agents: Vulnerabilities, Evaluation Containment, and Defensive Response

arXiv:2607.25379v1 Announce Type: new Abstract: Cyber-capable AI agents combine language models with tools, memory, and execution en- vironments to perform multi-step offensive-security tasks. Existin

DynaBridge: Dynamic Summary-Guided Cross-Task Multimodal Fusion for DASS-Structured Mental Health Assessment

arXiv:2607.25679v1 Announce Type: cross Abstract: Multimodal behavioral analysis offers a scalable approach to assessing depression, anxiety, and stress, yet generic fusion models often ignore the psy

researcharxiv-cs-ai

FinAbstain: Uncertainty-Calibrated Multimodal RAG for Selective Financial Forecasting

arXiv:2607.24875v1 Announce Type: new Abstract: Large language models (LLMs) can synthesize financial narratives but may express high confidence when evidence is sparse, stale, or contradictory. This

From Naive RAG to Deep Agentic Retrieval: An Evolving Context Engineering Pipeline for Regulatory Compliance

arXiv:2607.24791v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) is the dominant paradigm for applying large language models (LLMs) to enterprise document corpora, yet naive impl

Graphs move from niche database to enterprise knowledge layer for AI systems

As generative AI matures beyond its early experimentation phase, enterprises are converging on a shared architecture for grounding large language models in trustworthy data: the enterprise knowledge l

applicationssiliconangle

Guardians and Offenders: A Survey on Harmful Content Generation and Safety Mitigation of LLM

arXiv:2508.05775v3 Announce Type: replace Abstract: Large Language Models (LLMs) have revolutionized content creation across digital platforms, offering unprecedented capabilities in natural language

safetyarxiv-cs-cl

HiSkill: Empowering LLM Agents with Hierarchical Skill Graphs

arXiv:2607.25853v1 Announce Type: new Abstract: Skills have become an important abstraction for enabling large language model (LLM) agents to reuse past experience in long-horizon interactive tasks. H

How a scalable intelligence layer turns enterprise data into production A

Enterprises are discovering that a scalable intelligence layer built on knowledge graphs delivers the institutional context that turns generic AI models into reliable production systems. As companies

applicationssiliconangle

How Often Should a Recommender Call an LLM? Value-Weighted Routing, Monitoring, and Seasonal Robustness

arXiv:2607.25068v1 Announce Type: new Abstract: Routing decisions between a cheap heuristic and an expensive large language model (LLM) are typically framed as a difficulty problem: send the hard case

applicationsarxiv-cs-ai

Impressive paper! It's on one of the hardest tasks for coding agents today. Of course, I am talking about kernel optimization. Coding agents…

Impressive paper! It's on one of the hardest tasks for coding agents today. Of course, I am talking about kernel optimization. Coding agents are usually not so great at this. Reasons: Unfamiliar low-l

local-aidair-ai--x

JKO-RAG: Distributional Retrieval as Wasserstein Free-Energy Gradient Flow

arXiv:2607.24776v1 Announce Type: cross Abstract: RAG pipelines return a ranked list of passages. We argue this is a mismatch: the downstream language model conditions on a set, and the selection prob

Knowledge-Guided Multimodal Reasoning over Interacting Streams for Video-Level Ambivalence and Hesitancy Recognition

arXiv:2607.25961v1 Announce Type: cross Abstract: Ambivalence and hesitancy (A/H) are conflicting affective states that precede the delay or abandonment of health behaviour change. Recognition of A/H

researcharxiv-cs-ai

Language as a Material Interface for Creative LLM Interaction

arXiv:2607.24753v1 Announce Type: cross Abstract: Although directive prompting is the predominant way to interact with Large Language Models (LLMs), many creative practices rely on language that is op

researcharxiv-cs-cl

MARS: Multi-Agent Re-ranking for Repeat-Order Food Delivery Recommendation

arXiv:2607.25420v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used in recommender systems, but it is often unclear how much performance can be obtained from strong pr

local-aiarxiv-cs-ai

Industry

OpenAI president says it’s ‘building a family of devices’ for its AI chatbots

In an interview with our friend Joanna Stern on her YouTube channel, OpenAI president Greg Brockman said the company is working on a 'family of devices' for interacting with its AI models. However, Br

industrythe-verge-ai

Tutorials

Preliminary Guidelines for Using and Evaluating GenAI Tools to Support Systematic Literature Reviews

arXiv:2607.24991v1 Announce Type: cross Abstract: Context: Generative AI (GenAI) and Large Language Models (LLMs) are increasingly used for academic tasks in software engineering and beyond, including

tutorialsarxiv-cs-ai

ProcAgent: An Agentic Framework for Procedural Task Guidance on Edge with Human-in-the-Loop

arXiv:2607.24770v1 Announce Type: new Abstract: Procedural tasks such as furniture assembly and home repair impose substantial cognitive demands because users must interpret instructions, track task p

local-aiarxiv-cs-ai