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SynManDex: Synthesizing Human-like Dexterous Grasps from Synthetic Human Pre-Grasps

arXiv:2606.09798v1 Announce Type: new Abstract: Human hand-object interactions encode functional intent, but direct transfer to robotic hands often fails under morphology, contact, and reachability co

researcharxiv-cs-ro

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Applications

Synthetic but Not Realistic: The Evaluation Challenge in Generative Modelling for Structured Electronic Medical Records

DGX agent

arXiv:2606.08903v1 Announce Type: new Abstract: Synthetic healthcare data are widely proposed as privacy-preserving substitutes for real patient data, yet their evaluation remains dominated by statist

applicationsarxiv-cs-lg

9 Jun 2026

SynthICL: Scalable In-context Imitation Learning with Synthetic Data

arXiv:2606.08154v1 Announce Type: new Abstract: In-context imitation learning (ICIL) enables robots to learn new tasks from a small number of demonstrations by conditioning a pre-trained policy on tas

safetyarxiv-cs-ro

Systematic LLM Translation of Legacy Scientific Code to Differentiable Frameworks: Application to a Land Surface Model

arXiv:2606.07681v1 Announce Type: cross Abstract: Differentiable programming offers transformative capabilities for scientific modeling, enabling gradient-based parameter estimation, sensitivity analy

Systems-Level Planning and Coordination of Truck-Drone Collaborative Delivery Networks

arXiv:2606.08738v1 Announce Type: cross Abstract: Urban last-mile parcel delivery increasingly relies on heterogeneous fleets whose performance depends on timely coordination, reliable communication,

safetyarxiv-cs-ro

TABVERSE: Benchmarking Cross-Format Table Understanding in LLMs and VLMs

arXiv:2606.09578v1 Announce Type: new Abstract: Large Language Models (LLMs) and Vision-Language Models (VLMs) are increasingly evaluated on table reasoning tasks, but the role of table representation

TAME: A Trustworthy Test-Time Evolution of Agent Memory with Systematic Benchmarking

arXiv:2602.03224v2 Announce Type: replace Abstract: Test-time evolution of agent memory represents a pivotal paradigm for advancing AGI, as it strengthens complex reasoning through experience accumula

Agents

Taming Perception Jitter: Uncertainty-Aware LiDAR Object Detection for Reliable Motion Classification

arXiv:2606.09350v1 Announce Type: cross Abstract: Reliable motion classification is critical for autonomous driving, as false dynamic predictions of static objects can cascade into unnecessary planner

agentsarxiv-cs-cv

TAMUNA: Doubly Accelerated Distributed Optimization under Partial Participation

arXiv:2302.09832v4 Announce Type: replace Abstract: In distributed optimization and federated learning, slow and costly communication between parallel devices and the central server constitutes the pr

local-aiarxiv-cs-lg

Hardware

TAO: Tolerance-Aware Optimistic Verification for Floating-Point Neural Networks

arXiv:2510.16028v4 Announce Type: replace-cross Abstract: Neural networks increasingly run on hardware outside the user's control (cloud GPUs, inference marketplaces). Yet ML-as-a-Service reveals litt

hardwarearxiv-cs-ai

Targeting World Models to Compromise Robot Learning Pipelines

arXiv:2606.09499v1 Announce Type: cross Abstract: World models have recently seen a rapid growth in both their popularity and capability as more data efficient tools for generating robot training data

TBD-VLA: Temporal Block Diffusion Vision Language Action Model

arXiv:2606.07895v1 Announce Type: new Abstract: Discrete Vision-Language-Action (VLA) models typically formulate action generation as next-token prediction over discretized action spaces, conditioning

applicationsarxiv-cs-cv

Teacher-Free Self-Training Amplifies but Does Not Compound: A Pass@K Crossover on a Free-Verifier Domain

arXiv:2606.07856v1 Announce Type: new Abstract: When a language model trains on its own verified outputs, does it acquire capability beyond its base, or merely get better at expressing capability the

local-aiarxiv-cs-lg

TeamHerald@CHIPSAL 2026: Hate Speech Detection and Sentiment Analysis of Nepali Memes using Transformer-based Architectures and Ensemble Learning

arXiv:2606.08770v1 Announce Type: cross Abstract: The analysis of internet memes in the Nepali language is complicated by frequent code-mixing and a lack of established baseline resources. While memes

researcharxiv-cs-ai

Tools

@tejalpatwardhan this directly inspired my work at @cognition frontiercode https://x.com/jai_torregrosa/status/2064100437549072593?s=20

@tejalpatwardhan this directly inspired my work at @cognition frontiercode https://x.com/jai_torregrosa/status/2064100437549072593?s=20 props for including your own model on the chart. it's making a t

toolsswyx--x

TempoBench: Evaluating Temporal Causal Reasoning in Large Language Models

arXiv:2510.27544v2 Announce Type: replace Abstract: Temporal reasoning involves understanding how systems evolve over time through input-driven state transitions. A key aspect is temporal causal reaso

Temporal-Aware Reasoning Optimization for Video Temporal Grounding

arXiv:2606.09248v1 Announce Type: new Abstract: Multi-modal Large Language Models (MLLMs) have achieved remarkable progress in video temporal grounding with reinforcement learning for generating reaso

local-aiarxiv-cs-cv

Temporal Coverage over Density: Parsimonious Training-Set Design for ML Climate Downscaling

arXiv:2606.07898v1 Announce Type: new Abstract: High-resolution regional climate simulations provide critical information for climate impacts assessments but remain computationally expensive, motivati

Tensorizing Engram: Sharing Latents Across N-Gram Embeddings is Beneficial in LLMs

arXiv:2606.08347v1 Announce Type: cross Abstract: Modern language models represent text using discrete token-level embeddings, which forces recurring multi-token patterns to be learned implicitly acro

Tesla AI chip design engineering reviews are so great! Team is awesome. Our AI6 chip might set a record for most amount of usable intelligen…

Elon Musk posted on X about Tesla's AI chip design engineering team and their work on the AI6 chip, expressing confidence in the team's performance and suggesting the chip could achieve notable capabi

industryelon-musk--x

Test-Time Adaptive Composition for Machine Learning as a Service (MLaaS) in IoT Environments

arXiv:2606.07685v1 Announce Type: cross Abstract: The dynamic nature of Internet of Things (IoT) environments affects the long-term effectiveness of Machine Learning as a Service (MLaaS) compositions.

researcharxiv-cs-ai

Test-Time Scaling in Multimodal Foundation Models: A Comprehensive Survey of Generation and Reasoning

arXiv:2606.08231v1 Announce Type: new Abstract: Test-time Scaling (TTS) has emerged as a pivotal research direction for enhancing model performance by dynamically allocating computational resources du

researcharxiv-cs-cv

Testing the Black Box: Structural Barriers to Independent Evaluation of Consumer-Facing Health LLMs

arXiv:2606.08483v1 Announce Type: new Abstract: Background: Consumer-facing large language models are now a common source of health information, and they interpret and personalize responses rather tha

The ACUTE Protocol: Operationalizing Language Model Activations for Better Calibration, Utility, and Trust

arXiv:2606.07822v1 Announce Type: cross Abstract: As language models improve and become increasingly deployed to solve a variety of tasks, trustworthiness becomes essential. Calibration is a good prox

The AI Epistemic Deference Index: A Continuous Measure of Sycophancy

arXiv:2606.07897v1 Announce Type: new Abstract: Current AI models frequently exhibit epistemic sycophancy, endorsing claims to agree with a user. Existing evaluations typically measure this either by

The AI supersystem shift: Why Arista’s 1.6T announcement is an Ethernet inflection point

The networking industry loves inflection points. Over the years, we have had many new compute models that require the network to evolve. For as long as I can remember, the holy war between InfiniBand

industrysiliconangle

The best AI infrastructure shouldn't be reserved for the biggest companies. Together AI is partnering with @pax8 to bring powerful, cost-eff…

applicationstogether-ai--x

The best AI infrastructure shouldn't be reserved for the biggest companies. Together AI is partnering with @pax8 to bring powerful, cost-efficient AI and leading open-source models to small and mid-si

Tutorials

The CIFAR Synthetic Evidence Corpus for Detecting AI-Generated Evidence

arXiv:2606.07916v1 Announce Type: new Abstract: The growing ability of generative models to produce realistic documents poses a direct challenge to evidentiary workflows in the justice system and the

tutorialsarxiv-cs-ai

The Confidence Trap: Calibration Attacks for Graph Neural Networks

arXiv:2606.08467v1 Announce Type: cross Abstract: While confidence calibration is essential for trustworthy decision-making in safety-critical applications, the robustness of calibrated GNNs to advers

Agents

// The Consistency Illusion // Multi-agent debate can make agents agree on the final answer while their underlying reasoning stays misaligne…

// The Consistency Illusion // Multi-agent debate can make agents agree on the final answer while their underlying reasoning stays misaligned. This work finds that consensus on the output hides disagr

agentsdair-ai--x

The Cross-Architecture Substrate: A Domain-Transcendent, Calibration-Surviving Geometric Invariant of Modern Vision Encoders

arXiv:2606.07882v1 Announce Type: cross Abstract: Different vision neural networks -- trained to classify, contrast, reconstruct, or match images to text -- should have correspondingly different inter

The Download: whole-body rejuvenation drugs and five things to know about AI

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. David Sinclair plans to test whole-body rejuvenation drugs in

researchmit-tech-review

The Easy, the Hard, and the Learnable: Confidence and Difficulty-Adaptive Policy Optimization for LLM Reasoning

arXiv:2606.07950v1 Announce Type: new Abstract: RL with verifiable rewards can substantially improve LLM reasoning, yet standard GRPO-style training often treats easy, hard, and learnable questions al

safetyarxiv-cs-lg

The EU warns that AI-boosted chemical synthesis is helping European drug gangs develop new 'designer' drug precursors that evade existing product blacklists (Michael Peel/Financial Times)

Michael Peel / Financial Times: The EU warns that AI-boosted chemical synthesis is helping European drug gangs develop new “designer” drug precursors that evade existing product blacklists — EU agency

industrytechmeme

The evidence of two tier policing and judiciary is clear for all to see.

This post claims that there is evident disparity in how the police and judicial system treat different groups or individuals. The assertion suggests systemic inconsistency in law enforcement and court

industryelon-musk--x

The fact that Anthropic may take away subscription access to Fable in two weeks is weird & discourages investing in learning about the model…

applicationsethan-mollick--x

The fact that Anthropic may take away subscription access to Fable in two weeks is weird & discourages investing in learning about the model. Subscription use is how you figure out what the model is g

The Flexibility Trap: Rethinking the Value of Arbitrary Order in Diffusion Language Models

arXiv:2601.15165v4 Announce Type: replace-cross Abstract: Diffusion Large Language Models (dLLMs) break the rigid left-to-right constraint of traditional LLMs, enabling token generation in arbitrary o

The Governance of Human-LLM Interaction: Safety Gating, Civility Steering, and Affective Default Lock-In

arXiv:2606.08172v1 Announce Type: cross Abstract: Large language models (LLMs) increasingly mediate high-stakes interactions in finance, medicine, and mental-health support, yet users have limited con

The Hidden Bias of Process Reward Models:PRISM for Rewarding the Right Reasoning

arXiv:2606.09078v1 Announce Type: new Abstract: Process Reward Models (PRMs) improve credit assignment for reasoning by providing step-level feedback. However, we identify a hidden bias in PRMs caused

safetyarxiv-cs-lg

The Injection Paradox: Brand-Level Suppression in Safety-Trained LLM Recommendations via RAG Context Injection

model-releasesarxiv-cs-lg

arXiv:2606.09204v1 Announce Type: new Abstract: We present a reproducible failure mode of safety training in RAG-based LLM recommendation -- the Injection Paradox -- in which prompt injections embedde

The Label Horizon Paradox: Rethinking Supervision Targets in Financial Forecasting

arXiv:2602.03395v4 Announce Type: replace Abstract: While deep learning has revolutionized financial forecasting through sophisticated architectures, the design of the supervision signal itself is rar

The Last Visible Pixel: Probing Fine-Scale Perception in Vision-Language Models

arXiv:2606.07861v1 Announce Type: cross Abstract: Recent vision-language models (VLMs) excel at multimodal understanding and reasoning, yet their fine-grained visual perception remains underexplored.

The Mirrored Influence Hypothesis: Efficient Data Influence Estimation by Harnessing Forward Passes

arXiv:2402.08922v3 Announce Type: replace Abstract: Large-scale black-box models have become ubiquitous across numerous applications. Understanding the influence of individual training data sources on

The Montparnasse Algorithm for RNA Design

arXiv:2606.07562v1 Announce Type: cross Abstract: RNA design consists of discovering a nucleotide sequence that optimizes predefined criteria, such as secondary structure. It is useful for synthetic b

The Need for Neural ISP in the Small-Pixel Era: How Shrinking Pixels Push Optics to the Limit and Neural Restoration Pushes Back

arXiv:2606.07675v1 Announce Type: cross Abstract: Smartphone telephoto cameras are approaching a 'telephoto physics wall': as pixel pitches shrink toward sub-0.5 micron, the optics remain limited by g

local-aiarxiv-cs-cv

The New York Times published a roundtable discussion between @DAcemogluMIT, @deanwball, @clarashih & myself about the future of AI & who win…

applicationsethan-mollick--x

The New York Times published a roundtable discussion between @DAcemogluMIT, @deanwball, @clarashih & myself about the future of AI & who wins at work. I think it is a really nice overview of the core

Tutorials

The Routing Plateau: Understanding and Breaking the Accuracy Limits of LLM Routers

arXiv:2606.07587v1 Announce Type: new Abstract: LLM routing has become a popular approach to improve the cost-quality trade-off of LLM services by dynamically selecting a model for each query. Recent

tutorialsarxiv-cs-lg

The Sample Complexity of Parameter-Free Stochastic Convex Optimization

model-releasesarxiv-cs-lg

arXiv:2506.11336v2 Announce Type: replace Abstract: We study the sample complexity of stochastic convex optimization when problem parameters such as the distance to optimality and the Lipschitz consta