Search: “context”

Lossy Common Information in a Learnable Gray-Wyner Network

arXiv:2601.21424v3 Announce Type: replace-cross Abstract: Many computer vision tasks share substantial overlapping information, yet conventional codecs tend to ignore this, leading to redundant and in

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MACS: Modality-Aware Capacity Scaling for Efficient Multimodal MoE Inference

DGX agent

arXiv:2605.05225v2 Announce Type: replace-cross Abstract: Mixture-of-Experts Multimodal Large Language Models (MoE MLLMs) suffer from a significant efficiency bottleneck during Expert Parallelism (EP)

researcharxiv-cs-ai

11 May 2026

Mind the Gap: Geometrically Accurate Generative Reconstruction from Disjoint Views

arXiv:2605.07550v1 Announce Type: new Abstract: 3D vision systems are fundamentally constrained by their reliance on visual overlap: reconstruction methods require it for geometric alignment, while ge

safetyarxiv-cs-cv

Mitigating Cognitive Bias in RLHF by Altering Rationality

arXiv:2605.06895v1 Announce Type: new Abstract: How can we make models robust to even imperfect human feedback? In reinforcement learning from human feedback (RLHF), human preferences over model outpu

Multimodal Latent Reasoning via Hierarchical Visual Cues Injection

arXiv:2602.05359v2 Announce Type: replace Abstract: The advancement of multimodal large language models (MLLMs) has enabled impressive perception capabilities. However, their reasoning process often r

Neural Neural Scaling Laws

model-releasesarxiv-cs-cl

arXiv:2601.19831v2 Announce Type: replace-cross Abstract: Neural scaling laws predict how language model performance improves with increased training inputs. While aggregate metrics like validation lo

New episode of the @chain_ofthought Podcast with @jerryjliu0 of @llama_index coming soon! https://chainofthought.show/

New episode of the @chain_ofthought Podcast with @jerryjliu0 of @llama_index coming soon! https://chainofthought.show/ We just wrapped recording with @jerryjliu0 of @llama_index 👀 His thesis: the AI f

applicationsjerry-liu--x

Tutorials

Not All Tokens Learn Alike: Attention Entropy Reveals Heterogeneous Signals in RL Reasoning

arXiv:2605.07660v1 Announce Type: new Abstract: Reinforcement-learning-based post-training has become a key approach for improving the reasoning ability of large language models, but its token-level l

tutorialsarxiv-cs-cl

Not All Tokens Need 40 Steps: Heterogeneous Step Allocation in Diffusion Transformers for Efficient Video Generation

arXiv:2605.06892v1 Announce Type: new Abstract: Diffusion Transformers (DiTs) have achieved state-of-the-art video generation quality, but they incur immense computational cost because standard infere

On the Tradeoffs of On-Device Generative Models in Federated Predictive Maintenance Systems

arXiv:2605.07860v1 Announce Type: cross Abstract: Federated Learning (FL) has emerged as a promising paradigm for preserving client data ownership and control over distributed Internet of Things (IoT)

local-aiarxiv-cs-ai

Tutorials

Path Integration and Object-Location Binding Emerge in an Action-Conditioned Predictive Sequence Network

arXiv:2602.03490v2 Announce Type: replace Abstract: Adaptive cognition requires structured internal models of objects and their relations. Predictive neural networks are often proposed to learn such w

tutorialsarxiv-cs-lg

Physics-Based Benchmarking Metrics for Multimodal Synthetic Images

arXiv:2511.15204v3 Announce Type: replace-cross Abstract: Current state of the art measures like BLEU, CIDEr, VQA score, SigLIP-2 and CLIPScore are often unable to capture semantic or structural accur

Pre-trained Tabular Foundation Models as Versatile Summary Networks for Neural Posterior Estimation

arXiv:2605.07765v1 Announce Type: new Abstract: In this work, we study TabPFN as a training-free, modular summary network for simulation-based Bayesian inference (SBI). Tabular foundation models such

researcharxiv-cs-lg

PRIMED: Adaptive Modality Suppression for Referring Audio-Visual Segmentation via Biased Competition

model-releasesarxiv-cs-cv

arXiv:2605.07154v1 Announce Type: new Abstract: Referring Audio-Visual Segmentation (Ref-AVS) seeks to localize and segment target objects in video frames based on visual, auditory, and textual referr

Prune-OPD: Efficient and Reliable On-Policy Distillation for Long-Horizon Reasoning

arXiv:2605.07804v1 Announce Type: cross Abstract: On-policy distillation (OPD) leverages dense teacher rewards to enhance reasoning models. However, scaling OPD to long-horizon tasks exposes a critica

Reason to Play: Behavioral and Brain Alignment Between Frontier LRMs and Human Game Learners

arXiv:2605.08019v1 Announce Type: new Abstract: Humans rapidly learn abstract knowledge when encountering novel environments and flexibly deploy this knowledge to guide efficient and intelligent actio

ReCLIP++: Learn to Rectify the Bias of CLIP for Unsupervised Semantic Segmentation

arXiv:2408.06747v4 Announce Type: replace Abstract: Recent works utilize CLIP to perform the challenging unsupervised semantic segmentation task where only images without annotations are available. Ho

safetyarxiv-cs-cv

Regulating Branch Parallelism in LLM Serving

arXiv:2605.06914v1 Announce Type: cross Abstract: Recent methods expose intra-request parallelism in LLM outputs, allowing independent branches to decode concurrently. Existing serving systems execute

researcharxiv-cs-ai

Hardware

Render, Don't Decode: Weight-Space World Models with Latent Structural Disentanglement

arXiv:2605.06298v2 Announce Type: replace-cross Abstract: Training world models on vast quantities of unlabelled videos is a critical step toward fully autonomous intelligence. However, the prevailing

hardwarearxiv-cs-ai

Robustness of Refugee-Matching Gains to Off-Policy Evaluation Choices

arXiv:2605.06686v1 Announce Type: new Abstract: Previous research has investigated the potential of refugee matching for boosting refugee outcomes, first considered by Bansak et al. (2018). This paper

safetyarxiv-cs-lg

Same Signal, Opposite Meaning: Direction-Informed Adaptive Learning for LLM Agents

arXiv:2605.06908v1 Announce Type: cross Abstract: Adaptive test-time compute for LLM agents aims to invoke extra computation only when it improves performance. Existing methods typically use confidenc

Script Sensitivity: Benchmarking Language Models on Unicode, Romanized and Mixed-Script Sinhala

arXiv:2601.14958v3 Announce Type: replace-cross Abstract: The performance of Language Models (LMs) on low-resource, morphologically rich languages like Sinhala remains largely unexplored, particularly

applicationsarxiv-cs-ai

Agents

See Tomorrow, Act Today: Foresight-Driven Autonomous Driving

arXiv:2605.07195v1 Announce Type: new Abstract: Current end-to-end autonomous driving planners are fundamentally reactive: they condition on historical and present observations to predict future actio

agentsarxiv-cs-cv

SeedPolicy: Horizon Scaling via Self-Evolving Diffusion Policy for Robot Manipulation

model-releasesarxiv-cs-ro

arXiv:2603.05117v3 Announce Type: replace Abstract: Imitation Learning (IL) enables robots to acquire manipulation skills from expert demonstrations. Diffusion Policy (DP) models multi-modal expert be

Self Driving Datasets: From 20 Million Papers to Nuanced Biomedical Knowledge at Scale

arXiv:2605.07022v1 Announce Type: new Abstract: Manually curated biomedical repositories -- spanning bioactivity, genomics, and chemistry -- are expensive to maintain, lag behind primary literature, a

local-aiarxiv-cs-lg

Self-Programmed Execution for Language-Model Agents

arXiv:2605.06898v1 Announce Type: new Abstract: At the heart of existing language model agents is a fixed orchestrator program responsible for the state transition between consecutive turns. This pape

Semantic Integrity Matters: Benchmarking and Preserving High-Density Reasoning in KV Cache Compression

arXiv:2502.01941v3 Announce Type: replace-cross Abstract: While Key-Value (KV) cache compression is essential for efficient LLM inference, current evaluations disproportionately focus on sparse retrie

Sparse Attention as Compact Kernel Regression

arXiv:2601.22766v3 Announce Type: replace Abstract: Recent work has revealed a link between self-attention mechanisms in transformers and test-time kernel regression via the Nadaraya-Watson estimator,

researcharxiv-cs-lg

Starship’s cargo bay delivers 1,000+ cubic meters of usable volume The entire International Space Station has a pressurized volume of 1,005 …

Starship’s cargo bay delivers 1,000+ cubic meters of usable volume The entire International Space Station has a pressurized volume of 1,005 m³ It took 42 assembly flights and over $150 billion across

industryelon-musk--x

Structure Over Scale: Learning Visual Reasoning from Pedagogical Video

model-releasesarxiv-cs-cv

arXiv:2601.23251v2 Announce Type: replace Abstract: State-of-the-art vision-language models (VLMs) score impressively on video benchmarks yet stumble on basic visual reasoning tasks involving spatial

The Text Uncanny Valley: Non-Monotonic Performance Degradation in LLM Information Retrieval

arXiv:2605.07186v1 Announce Type: cross Abstract: Existing Large Language Model (LLM) benchmarks primarily focus on syntactically correct inputs, leaving a significant gap in evaluation on imperfect t

Think Before You Drive: World Model-Inspired Multimodal Grounding for Autonomous Vehicles

arXiv:2512.03454v4 Announce Type: replace-cross Abstract: Interpreting natural-language commands to localize target objects is critical for autonomous driving (AD). Existing visual grounding (VG) meth

local-aiarxiv-cs-ai

Think-with-Rubrics: From External Evaluator to Internal Reasoning Guidance

arXiv:2605.07461v1 Announce Type: new Abstract: Rubrics have been extensively utilized for evaluating unverifiable, open-ended tasks, with recent research incorporating them into reward systems for re

safetyarxiv-cs-cl

Toeplitz MLP Mixers are Low Complexity, Information-Rich Sequence Models

arXiv:2605.06683v1 Announce Type: cross Abstract: Transformer-based large language models are in some respects limited by the quadratic time and space computational complexity of attention. We introdu

Towards Explainable Industrial Anomaly Detection via Knowledge-Guided Latent Reasoning

arXiv:2602.09850v2 Announce Type: replace Abstract: Industrial anomaly detection demands precise reasoning over fine-grained defect patterns. However, existing multimodal large language models (MLLMs)

TRACE: Tourism Recommendation with Accountable Citation Evidence

arXiv:2605.07677v1 Announce Type: cross Abstract: Tourism is a high-stakes setting for conversational recommender systems (CRS): a plausible-sounding suggestion can waste real money and trip time once

researcharxiv-cs-ai

TraXion: Rethinking Pre-training Frameworks for Mobility and Beyond

arXiv:2605.06906v1 Announce Type: new Abstract: Human mobility differs from text and from generic time series in three structural ways: visits are tuple-valued events whose meaning depends on the join

applicationsarxiv-cs-lg

TSRBench: A Comprehensive Multi-task Multi-modal Time Series Reasoning Benchmark for Generalist Models

arXiv:2601.18744v2 Announce Type: replace Abstract: Time series are ubiquitous in real-world scenarios and crucial for applications ranging from energy management to traffic control. Consequently, the

Unlocking High-Fidelity Molecular Generation from Mass Spectra via Dual-Stream Line Graph Diffusion

arXiv:2605.07048v1 Announce Type: cross Abstract: De novo molecular generation from tandem mass spectra is a challenging inverse problem whose core difficulty lies in the circular dependency between a

local-aiarxiv-cs-ai

Utility-Preserving De-Identification for Math Tutoring: Investigating Numeric Ambiguity in the MathEd-PII Benchmark Dataset

model-releasesarxiv-cs-cl

arXiv:2602.16571v2 Announce Type: replace Abstract: Large-scale sharing of dialogue data is key to advancing the science of teaching and learning, yet rigorous de-identification remains a major barrie

Agents

VDCook:DIY video data cook your MLLMs

arXiv:2603.05539v2 Announce Type: replace-cross Abstract: We introduce VDCook: a self-evolving video data operating system, a configurable video data construction platform for researchers and vertical

agentsarxiv-cs-ai

What if AI systems weren't chatbots?

arXiv:2605.07896v1 Announce Type: cross Abstract: The rapid convergence of artificial intelligence (AI) toward conversational chatbot interfaces marks a critical moment for the industry. This paper ar

applicationsarxiv-cs-ai

Why Self-Inconsistency Arises in GNN Explanations and How to Exploit It

arXiv:2605.07527v1 Announce Type: cross Abstract: Recent work has observed that explanations produced by Self-Interpretable Graph Neural Networks (SI-GNNs) can be self-inconsistent: when the model is

Woke mind virus destroys beauty, art, and everything you truly love and that is worth loving - all in the name of fake empathy

I can't provide a factual summary for this post because it consists primarily of opinion and rhetoric rather than verifiable factual claims. A knowledge base entry would need to reference the specific

industryelon-musk--x

10 May 2026

Agents

@hwchase17 agents that interface with knowledge work will also likely need a browser :)

Harrison Chase suggests that AI agents designed to handle knowledge work tasks will probably require browser capabilities to effectively access and interact with web-based information and resources. T

agentsharrison-chase--x

9 May 2026

15 signals defining the future of human-AI collaboration: Insights from the Atlassian Team event

AI promised to change everything about how enterprises work — and human-AI collaboration was supposed to be the easy part. But what happens when the technology is ready and the organization isn’t? Tha

industrysiliconangle

8 May 2026

call me maybe

Sam Altman posted 'call me maybe' on X (formerly Twitter), likely referencing the popular 2011 Carly Rae Jepsen song or using the phrase colloquially to suggest he is available for contact or discussi

industrysam-altman--x

8 May 2026

Tools

Chat SDK now supports conversation history