All entries

Self-Distillation Enables Continual Learning

arXiv:2601.19897v2 Announce Type: replace Abstract: Continual learning, enabling models to acquire new skills and knowledge without degrading existing capabilities, remains a fundamental challenge for

safetyarxiv-cs-lg

Semantic Adapter Routing with Fine-Tuning Task Embeddings

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arXiv:2606.19079v2 Announce Type: replace Abstract: Parameter-efficient fine-tuning (PEFT) has led to model ecosystems in which a single backbone is paired with many task-specialized adapters. Given s

model-releasesarxiv-cs-ai

10 Aug 2026

Semi Edge Inference Idea [D]

tutorialsr-machinelearning

Today the most important factor in AI is cost. My idea is to split ML models inference (closed ones, proprietary) across server and edge computing on clients, and I would like to hear what do you thin

Separating Decision-Rule Misalignment from Readout-Coverage Limitations in Speech Language Models

arXiv:2608.06409v1 Announce Type: cross Abstract: Speech language models are increasingly evaluated on paralinguistic tasks by the accuracy of prompted answers, but answer accuracy combines failures a

SetEasy: A Multi-Modal Classroom Engagement Assessment and Seating Optimization Framework

arXiv:2608.07188v1 Announce Type: new Abstract: SetEasy optimizes classroom engagement in fixed seating grids. It fuses multimodal sensing (wristband physiology, 4K video, environmental data) and trai

Shape Your Feed: An LLM-based Agentic System for Conversational Recommendation

arXiv:2608.06632v1 Announce Type: new Abstract: Industrial recommendation systems predominantly adopt a passive ranking paradigm that infers user preferences from implicit behavioral signals (e.g., cl

safetyarxiv-cs-ai

Applications

Sharding Prevents LLM Oversight Failures and Adversarial Exploitation

arXiv:2608.06422v1 Announce Type: new Abstract: Giving an LLM judge more compute does not necessarily make it check more requirements. When one call must return many verdicts, some decisions become we

applicationsarxiv-cs-lg

Simple-OPD: Demystifying Warm-up for On-policy Distillation

model-releasesarxiv-cs-cl

arXiv:2608.06802v1 Announce Type: new Abstract: On-policy distillation (OPD) trains a student on its own rollouts with token-level supervision from teacher models, but its effectiveness can depend str

SimWAM: A Simple World Action Model for End-to-End Autonomous Driving

arXiv:2608.07468v1 Announce Type: new Abstract: World-Action Models (WAMs) improve end-to-end autonomous driving by transferring video dynamics priors to action prediction, but existing methods requir

agentsarxiv-cs-cv

Skaling: Chinchilla's Exponents Meet Kaplan's Coupling

arXiv:2608.07222v1 Announce Type: new Abstract: Neural scaling laws are foundational for language model development, yet standard formulations systematically under- and overestimate loss at data-scarc

researcharxiv-cs-cl

SkillAligner: Treating Retrieved Skills as Adaptable Drafts at Execution Time

arXiv:2608.06880v1 Announce Type: new Abstract: General-purpose skills promise reusable procedural knowledge for language agents, yet semantic relevance does not guarantee execution utility: a retriev

agentsarxiv-cs-lg

SkillEval: Decomposing Agent Skill Quality into Interpretable Signals

arXiv:2608.06891v1 Announce Type: new Abstract: Agent skills provide reusable procedural knowledge that helps agents solve specialized tasks. As their use expands, evaluating skill quality becomes inc

SkillProx: Self-Evolving Agent Skills via Proximal Textual Gradient Descent

arXiv:2608.07449v1 Announce Type: new Abstract: LLM agents increasingly adapt to recurring tasks by accumulating procedural knowledge in skills. These skills are lightweight, reusable textual artifact

SkySeaLand: A Wide-Format Satellite Transportation Benchmark with an Ultra-Lightweight Detection Baseline

arXiv:2608.07382v1 Announce Type: new Abstract: Satellite object detection is challenged by small targets and wide-format scenes that lose detail under standard square-input resizing. We introduce Sky

SLED: Scalable Location Encoding via Distillation

arXiv:2608.06612v1 Announce Type: cross Abstract: The plethora of readily available geospatial data offers exciting opportunities to learn high quality representations of the planet, but the sheer siz

SNI-GNN: SmartNIC-Assisted Full-Graph GNN Training with In-Network Embedding Prediction

arXiv:2608.06441v1 Announce Type: new Abstract: Full-graph GNN training delivers high accuracy but scales poorly on multi-server clusters due to heavy, irregular inter-node embedding exchanges. We pre

safetyarxiv-cs-lg

Social World Models

arXiv:2509.00559v3 Announce Type: replace Abstract: Humans intuitively navigate social interactions by simulating unspoken dynamics and reasoning about others' perspectives, even with limited informat

Soft Redaction of Image Provenance via Zero-Knowledge Proofs

arXiv:2608.07063v1 Announce Type: cross Abstract: Content provenance standards, such as C2PA, are increasingly used to attach signed records of origin, editing history, and rights to digital images. H

Solver-Guided Reasoning for Mixed-Equilibrium Strategies

arXiv:2608.06741v1 Announce Type: new Abstract: Reasoning in large language models (LLMs) is often grounded in human text, human demonstrations, and human-generated rationales. For equilibrium reasoni

tutorialsarxiv-cs-lg

SoRoMoX: Fast, Differentiable, and Parallelizable Soft Robot Models

arXiv:2608.06650v1 Announce Type: cross Abstract: Reduced-order models based on Cosserat-rod theory are now well established, and modeling theory is no longer the primary bottleneck in soft-robot cont

safetyarxiv-cs-ai

Hardware

Sources: AI cloud computing provider Lambda is selling a $917M leveraged loan to finance the purchase of GPUs as part of a contract with Nvidia (Bloomberg)

Bloomberg: Sources: AI cloud computing provider Lambda is selling a $917M leveraged loan to finance the purchase of GPUs as part of a contract with Nvidia — Lambda Inc., an AI cloud-computing provider

hardwaretechmeme

Industry

Sources: Anthropic agreed to a 20-year, $9.1B compute deal with Riot Platforms for 191 MW of capacity at a Rockdale, TX campus; RIOT jumps ~25% after hours (Shirin Ghaffary/Bloomberg)

Shirin Ghaffary / Bloomberg: Sources: Anthropic agreed to a 20-year, 9.1B compute deal with Riot Platforms for 191 MW of capacity at a Rockdale, TX campus; RIOT jumps ~25% after hours — Anthropic PBC

industrytechmeme

Sources: officials say OpenAI risks its White House relationship by hiring Dean Ball, who has criticized Trump's AI strategy after leaving the administration (Thomas Barrabi/New York Post)

Thomas Barrabi / New York Post: Sources: officials say OpenAI risks its White House relationship by hiring Dean Ball, who has criticized Trump's AI strategy after leaving the administration — Top Open

safetytechmeme

Industry

Sources: the AI-driven memory chip shortage has kicked off a rush of DC lobbying; many US officials appear unsympathetic to Apple's desire to buy Chinese chips (New York Times)

New York Times: Sources: the AI-driven memory chip shortage has kicked off a rush of DC lobbying; many US officials appear unsympathetic to Apple's desire to buy Chinese chips — The artificial intelli

industrytechmeme

SparseVoxelDet: Fully Sparse Voxel Networks for Efficient Event-Based Drone Detection

arXiv:2603.21638v2 Announce Type: replace Abstract: Event cameras excel at detecting small, fast drones, but today's detectors give away their key advantage: they convert the sparse event stream into

Spatiotemporal Agility: Time-Constrained Reinforcement Learning for Vision-Guided Dynamic Quadrupedal Interception

model-releasesarxiv-cs-ro

arXiv:2608.06907v1 Announce Type: new Abstract: Legged robots require robust agility to perceive and interact with complex and dynamic environments within a constrained time. However, most existing qu

Stability of Transformers under Layer Normalization

arXiv:2510.09904v2 Announce Type: replace-cross Abstract: Despite their widespread use, training deep Transformers can be unstable. Layer normalization, a standard component, improves training stabili

Stable Curves, Unstable Items: Item-Level Scaling Heterogeneity in Video LLMs

arXiv:2608.07014v1 Announce Type: new Abstract: Aggregate scaling curves suggest that Video LLMs improve smoothly or saturate as visual budgets grow. We show that this view can conceal large, opposing

StepJack: Benchmarking Computer-Use Agent Safety Against Multi-Step Indirect Prompt Injection

arXiv:2608.06477v1 Announce Type: cross Abstract: Computer-use agents (CUAs) face a growing threat from indirect prompt injection, where adversarial instructions are planted in the environment such as

Stochastic Autoregressive Learning

arXiv:2608.07224v1 Announce Type: new Abstract: Motivated by LLMs, which generate outputs by iteratively sampling from next-token distributions, we introduce a PAC-learning model for binary stochastic

tutorialsarxiv-cs-lg

Stockmark-Nemotron-3-Nano-Omni-JapanDocReader: Structured Document Parsing via Capability Injection and Forgetting Control

model-releasesarxiv-cs-cl

arXiv:2608.06758v1 Announce Type: new Abstract: We present Stockmark-Nemotron-3-Nano-Omni-JapanDocReader, a Japanese document understanding model built from Nemotron-3-Nano-Omni-30B-A3B-Reasoning-BF16

Stoicheia: Character-Level Masked Diffusion for Ancient Greek Textual Restoration, Parsing, and Metrical Scansion

model-releasesarxiv-cs-cl

arXiv:2608.07249v1 Announce Type: new Abstract: We introduce Stoicheia, a 405M-parameter character-level masked-diffusion encoder for Ancient Greek whose input factors into five aligned, independently

Strategy-first synthesis planning for complex natural products

arXiv:2608.07454v1 Announce Type: cross Abstract: The total synthesis of a complex molecule is among the most demanding intellectual and experimental feats in chemistry: a chemist must plan many steps

Local Ai

Stream Learning: Partition-Fair Gossip Learning Without Tokens

arXiv:2608.06946v1 Announce Type: cross Abstract: In gossip learning, a network of nodes trains a shared model collaboratively, without a central coordinator, by repeatedly exchanging parts of their l

local-aiarxiv-cs-lg

Sub-Quadratic Bisimulation Metrics via Approximate Nearest Neighbors: Coverage-Augmented Guarantees and Computable Two-Sided Certificates

model-releasesarxiv-cs-lg

arXiv:2608.06762v1 Announce Type: new Abstract: Bisimulation metrics quantify behavioral similarity in Markov decision processes, but their Wasserstein fixed-point operator updates every state pair an

SubtleTalk: Generating Controllable Weakly-correlated Facial Dynamics for 3D Talking Heads via Residual Flow Matching

arXiv:2608.06408v1 Announce Type: cross Abstract: Audio-driven 3D facial animation aims to synthesize realistic and temporally coherent motions from speech. Despite notable progress in lip synchroniza

researcharxiv-cs-cv

Hardware

Summarize First, Download Later: Onboard VLMs for Bandwidth-Efficient Earth Observation

arXiv:2608.06959v1 Announce Type: new Abstract: Modern Earth observation (EO) satellites carry increasingly advanced sensors that produce vast volumes of high-resolution, multispectral data, yet downl

hardwarearxiv-cs-cv

Summary of Takeaways from the Minimax AMA

model-releasesr-stablediffusion

Summary from https://www.reddit.com/r/StableDiffusion/comments/1vh9rtw/ama_minimax_h3_team_ask_us_anything_about_our/ This summary was compiled with AI but cross-checked manually by me for accuracy. I

Suppress and Diversify: Refining Robust Pathways for Corruption Robustness

arXiv:2608.06712v1 Announce Type: new Abstract: Model robustness against natural image corruptions is essential for safety-critical applications. While existing methods primarily focus on implicit rep

Surg-UniWorld: A Unified Surgical World Model with Multimodal Control Experts

arXiv:2608.06770v1 Announce Type: new Abstract: Controllable surgical world models can provide a generative foundation for surgical artificial intelligence and simulation by synthesizing realistic ins

Symbolic Graphics Programming with Large Language Models

arXiv:2509.05208v2 Announce Type: replace Abstract: Large language models (LLMs) excel at program synthesis, yet their ability to produce symbolic graphics programs (SGPs) that render into precise vis

SyncSBC: Decentralized Swarm Behavior Prediction for Synchronized Autonomous Control

arXiv:2608.06587v1 Announce Type: cross Abstract: Robot swarms utilize many independent limited-sensing agents to produce complex emergent behaviors without requiring centralized control. However, lit

Applications

Synthetic LiDAR Data Generation and Deterministic Downsampling for Point Cloud Classification on the Edge

arXiv:2608.07106v1 Announce Type: new Abstract: Deploying three-dimensional deep learning frameworks to low-power embedded processors is bottlenecked by the unstructured nature of spatial data and the

applicationsarxiv-cs-lg

TA-RAG: Tone Awareness as a Design Imperative for Retrieval-Augmented Generation

arXiv:2608.06672v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) has become a robust architecture for grounding large language models (LLMs) in trusted knowledge. However, standard

safetyarxiv-cs-cl

Target-Weighted Neyman Allocation: Experimental Design for Heterogeneous Treatment Effects under Population Shift

arXiv:2608.06512v1 Announce Type: new Abstract: Randomized experiments are often run in one population to guide decisions in another. Allocating by experimental proportions wastes budget on groups tha

tutorialsarxiv-cs-lg

TaskSense: Focusing on What Matters in World Models

arXiv:2608.06544v1 Announce Type: new Abstract: World models for visual control typically learn compact latent states by reconstructing observations, implicitly encouraging representations to preserve

tutorialsarxiv-cs-ai

Applications

Taxonomy-Driven Analysis of Open-Source AI Risk Mitigation Tools

arXiv:2608.07446v1 Announce Type: cross Abstract: Rapid adoption of large language models (LLMs) in enterprise settings has introduced operational, security, and governance risks. As generative AI app

applicationsarxiv-cs-ai

TEMPO: Semantic-Action Decoupled RL Post-Training for Vision-Language-Action Models

arXiv:2608.07314v1 Announce Type: cross Abstract: Vision-language-action (VLA) models are commonly adapted to downstream manipulation tasks via supervised fine-tuning (SFT) or online reinforcement lea