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Symmetry Guarantees Statistic Recovery in Variational Inference

arXiv:2604.18310v1 Announce Type: cross Abstract: Variational inference (VI) is a central tool in modern machine learning, used to approximate an intractable target density by optimising over a tracta

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SynAgent: Generalizable Cooperative Humanoid Manipulation via Solo-to-Cooperative Agent Synergy

DGX agent

arXiv:2604.18557v1 Announce Type: new Abstract: Controllable cooperative humanoid manipulation is a fundamental yet challenging problem for embodied intelligence, due to severe data scarcity, complexi

safetyarxiv-cs-cv

21 Apr 2026

SynopticBench: Evaluating Vision-Language Models on Generating Weather Forecast Discussions of the Future

arXiv:2604.16451v1 Announce Type: new Abstract: Recent advances in visual-language models (VLMs) have led to significant improvements in a plethora of complex multimodal tasks like image captioning, r

safetyarxiv-cs-cl

Synthetic Data Generation for Training Diversified Commonsense Reasoning Models

arXiv:2603.18361v2 Announce Type: replace Abstract: Conversational agents are required to respond to their users not only with high quality (i.e. commonsense bearing) responses, but also considering m

Tutorials

SynthFix: Adaptive Neuro-Symbolic Code Vulnerability Repair

arXiv:2604.17184v1 Announce Type: cross Abstract: Large Language Models (LLMs) show promise for automated code repair but often struggle with the complex semantic and structural correctness required.

tutorialsarxiv-cs-lg

Synthia: Scalable Grounded Persona Generation from Social Media Data

arXiv:2507.14922v2 Announce Type: replace Abstract: Persona-driven simulations are increasingly used in computational social science, yet their validity critically depends on the fidelity of the under

safetyarxiv-cs-cl

SynthPID: P&ID digitization from Topology-Preserving Synthetic Data

model-releasesarxiv-cs-cv

arXiv:2604.16513v1 Announce Type: new Abstract: Automating the digitization of Piping and Instrumentation Diagrams (P&IDs) into structured process graphs would unlock significant value in plant operat

Systematic Capability Benchmarking of Frontier Large Language Models for Offensive Cyber Tasks

arXiv:2604.17159v1 Announce Type: cross Abstract: We present, to our knowledge, the most comprehensive cross-model evaluation of LLM agents on offensive cybersecurity tasks, benchmarking 10 frontier m

Local Ai

T-REN: Learning Text-Aligned Region Tokens Improves Dense Vision-Language Alignment and Scalability

arXiv:2604.18573v1 Announce Type: new Abstract: Despite recent progress, vision-language encoders struggle with two core limitations: (1) weak alignment between language and dense vision features, whi

local-aiarxiv-cs-cv

Table Question Answering in the Era of Large Language Models: A Comprehensive Survey of Tasks, Methods, and Evaluation

arXiv:2510.09671v2 Announce Type: replace Abstract: Table Question Answering (TQA) aims to answer natural language questions about tabular data, often accompanied by additional contexts such as text p

TacticGen: Grounding Adaptable and Scalable Generation of Football Tactics

arXiv:2604.18210v1 Announce Type: cross Abstract: Success in association football relies on both individual skill and coordinated tactics. While recent advancements in spatio-temporal data and deep le

agentsarxiv-cs-lg

TagaVLM: Topology-Aware Global Action Reasoning for Vision-Language Navigation

model-releasesarxiv-cs-cv

arXiv:2603.02972v2 Announce Type: replace Abstract: Vision-Language Navigation (VLN) presents a unique challenge for Large Vision-Language Models (VLMs) due to their inherent architectural mismatch: V

Tailoring Diagnostic Modeling to Individual Learners: Personalized Distractor Generation via MCTS-Guided Reasoning Reconstruction

arXiv:2508.11184v2 Announce Type: replace Abstract: Distractors-incorrect yet plausible answer choices in multiple-choice questions (MCQs)-are vital in educational assessments, as they help identify s

Tape: A Cellular Automata Benchmark for Evaluating Rule-Shift Generalization in Reinforcement Learning

model-releasesarxiv-cs-lg

arXiv:2601.04695v2 Announce Type: replace-cross Abstract: Out-of-distribution generalization in reinforcement learning is hard to diagnose when benchmark shifts mix dynamics, observations, goals, and

Target Parameterization in Diffusion Models for Nonlinear Spatiotemporal System Identification

arXiv:2604.17566v1 Announce Type: cross Abstract: Machine learning is becoming increasingly important for nonlinear system identification, including dynamical systems with spatially distributed output

Task Matters: Knowledge Requirements Shape LLM Responses to Context-Memory Conflict

arXiv:2506.06485v4 Announce Type: replace Abstract: Large language models (LLMs) draw on both contextual information and parametric memory, yet these sources can conflict. Prior studies have largely e

safetyarxiv-cs-cl

TeleEmbedBench: A Multi-Corpus Embedding Benchmark for RAG in Telecommunications

model-releasesarxiv-cs-lg

arXiv:2604.17778v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed in the telecommunications domain for critical tasks, relying heavily on Retrieval-Augmented Gener

Temporal Representations for Exploration: Learning Complex Exploratory Behavior without Extrinsic Rewards

arXiv:2603.02008v2 Announce Type: replace Abstract: Effective exploration in reinforcement learning requires not only tracking where an agent has been, but also understanding how the agent perceives a

agentsarxiv-cs-lg

TeMuDance: Contrastive Alignment-Based Textual Control for Music-Driven Dance Generation

arXiv:2604.17005v1 Announce Type: new Abstract: Existing music-driven dance generation approaches have achieved strong realism and effective audio-motion alignment. However, they generally lack semant

safetyarxiv-cs-cv

TensorHub: Rethinking AI Model Hub with Tensor-Centric Compression

arXiv:2604.17104v1 Announce Type: cross Abstract: Modern AI models are growing rapidly in size and redundancy, leading to significant storage and distribution challenges in model hubs. We present Tens

applicationsarxiv-cs-lg

Test-Time Adaptation for EEG Foundation Models: A Systematic Study under Real-World Distribution Shifts

model-releasesarxiv-cs-lg

arXiv:2604.16926v1 Announce Type: new Abstract: Electroencephalography (EEG) foundation models have shown strong potential for learning generalizable representations from large-scale neural data, yet

Test-Time Alignment via Hypothesis Reweighting

arXiv:2412.08812v2 Announce Type: replace Abstract: Reward models trained on aggregate preferences often fail to capture individual users' values, but existing adaptation methods such as fine-tuning o

safetyarxiv-cs-lg

Test-Time Perturbation Learning with Delayed Feedback for Vision-Language-Action Models

arXiv:2604.18107v1 Announce Type: new Abstract: Vision-Language-Action models (VLAs) achieve remarkable performance in sequential decision-making but remain fragile to subtle environmental shifts, suc

researcharxiv-cs-cv

Test-Time Reasoners Are Strategic Multiple-Choice Test-Takers

arXiv:2510.07761v2 Announce Type: replace Abstract: Large language models (LLMs) now give reasoning before answering, excelling in tasks like multiple-choice question answering (MCQA). Yet, a concern

TextTIGER: Text-based Intelligent Generation with Entity Prompt Refinement for Text-to-Image Generation

arXiv:2504.18269v2 Announce Type: replace Abstract: When generating images from prompts that include specific entities, the model must retain as much entity-specific knowledge as possible. However, th

Textual Bayes: Quantifying Prompt Uncertainty in LLM-Based Systems

arXiv:2506.10060v2 Announce Type: replace Abstract: Although large language models (LLMs) are becoming increasingly capable of solving challenging real-world tasks, accurately quantifying their uncert

applicationsarxiv-cs-lg

TGLF-WINN: Data-Efficient Deep Learning Surrogate for Turbulent Transport Modeling in Fusion

arXiv:2509.07024v2 Announce Type: replace-cross Abstract: The Trapped Gyro-Landau Fluid (TGLF) model provides fast, accurate predictions of turbulent transport in tokamaks, but whole device simulation

That's my designer - Claude

model-releasesben-s-bites

This article from Ben's Bites likely discusses Claude, an AI assistant, in the context of design or designer tools, possibly exploring how Claude can assist with design work or comparing it to other d

The Breakthrough of Sleep: A Contactless Approach for Accurate Sleep Stage Detection Using the Sleepal AI Lamp

arXiv:2604.16442v1 Announce Type: cross Abstract: Sleep staging is essential for the assessment of sleep quality and the diagnosis of sleep-related disorders. Conventional polysomnography (PSG), while

applicationsarxiv-cs-lg

Tools

The 'bridge of authority' in RAG: ❌ LLMs can reason about 'blue skies' or 'purple skies' with the same authority. ✅ Vector DBs let you peer …

The 'bridge of authority' in RAG: ❌ LLMs can reason about 'blue skies' or 'purple skies' with the same authority. ✅ Vector DBs let you peer into the metadata to find the source/author. 'Do you trust a

toolspinecone--x

The Cognitive Penalty: Ablating System 1 and System 2 Reasoning in Edge-Native SLMs for Decentralized Consensus

arXiv:2604.16913v1 Announce Type: cross Abstract: Decentralized Autonomous Organizations (DAOs) are inclined explore Small Language Models (SLMs) as edge-native constitutional firewalls to vet proposa

The Collaboration Gap in Human-AI Work

arXiv:2604.18096v1 Announce Type: cross Abstract: LLMs are increasingly presented as collaborators in programming, design, writing, and analysis. Yet the practical experience of working with them ofte

Local Ai

The Consensus Trap: Rescuing Multi-Agent LLMs from Adversarial Majorities via Token-Level Collaboration

arXiv:2604.17139v1 Announce Type: new Abstract: Multi-agent large language model (LLM) architectures increasingly rely on response-level aggregation, such as Majority Voting (MAJ), to raise reasoning

local-aiarxiv-cs-cl

Tutorials

The Download: turning down human noise, and LA’s stunning subway upgrade

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. The noise we make is hurting animals. Can we learn to shut up?

tutorialsmit-tech-review

The First Challenge on Mobile Real-World Image Super-Resolution at NTIRE 2026: Benchmark Results and Method Overview

model-releasesarxiv-cs-cv

arXiv:2604.17306v1 Announce Type: new Abstract: This paper provides a review of the NTIRE 2026 challenge on mobile real-world image super-resolution, highlighting the proposed solutions and the result

The Gait Signature of Frailty: Transfer Learning based Deep Gait Models for Scalable Frailty Assessment

arXiv:2603.24434v2 Announce Type: replace Abstract: Frailty is a condition in aging medicine characterized by diminished physiological reserve and increased vulnerability to stressors. However, frailt

researcharxiv-cs-cv

The GDN-CC Dataset: Automatic Corpus Clarification for AI-enhanced Democratic Citizen Consultations

arXiv:2601.14944v3 Announce Type: replace Abstract: LLMs are ubiquitous in modern NLP, and while their applicability extends to texts produced for democratic activities such as online deliberations or

The Geometric Canary: Predicting Steerability and Detecting Drift via Representational Stability

arXiv:2604.17698v1 Announce Type: cross Abstract: Reliable deployment of language models requires two capabilities that appear distinct but share a common geometric foundation: predicting whether a mo

The Global Neural World Model: Spatially Grounded Discrete Topologies for Action-Conditioned Planning

arXiv:2604.16585v1 Announce Type: new Abstract: We present the Global Neural World Model (GNWM), a self-stabilizing framework that achieves topological quantization through balanced continuous entropy

agentsarxiv-cs-lg

The Illusion of Certainty: Decoupling Capability and Calibration in On-Policy Distillation

arXiv:2604.16830v1 Announce Type: new Abstract: On-policy distillation (OPD) is an increasingly important paradigm for post-training language models. However, we identify a pervasive Scaling Law of Mi

safetyarxiv-cs-lg

The Illusion of Insight in Reasoning Models

arXiv:2601.00514v2 Announce Type: replace-cross Abstract: Do reasoning models have 'Aha!' moments? Prior work suggests that models like DeepSeek-R1-Zero undergo sudden mid-trace realizations that lead

The Impact of Off-Policy Training Data on Probe Generalisation

arXiv:2511.17408v4 Announce Type: replace-cross Abstract: Probing has emerged as a promising method for monitoring large language models (LLMs), enabling cheap inference-time detection of concerning b

safetyarxiv-cs-lg

The impact of postediting on AI generative translation in Yemeni context: Translating literary prose by ChatGPT

arXiv:2604.16704v1 Announce Type: new Abstract: This study examines the role of artificial intelligence in translation, focusing on ChatGPT, specifically ChatGPT-4, and the extent to which human poste

The Landscape of Agentic Reinforcement Learning for LLMs: A Survey

arXiv:2509.02547v5 Announce Type: replace-cross Abstract: The emergence of agentic reinforcement learning (Agentic RL) marks a paradigm shift from conventional reinforcement learning applied to large

agentsarxiv-cs-cl

The Less You Depend, The More You Learn: Synthesizing Novel Views from Sparse, Unposed Images with Minimal 3D Knowledge

arXiv:2506.09885v2 Announce Type: replace Abstract: Recent advances in feed-forward Novel View Synthesis (NVS) have led to a divergence between two design philosophies: bias-driven methods, which rely

safetyarxiv-cs-cv

The Los Angeles Unified School District's board votes to require screen time limits, making it the first major American school system to do so (Tyler Kingkade/NBC News)

Tyler Kingkade / NBC News: The Los Angeles Unified School District's board votes to require screen time limits, making it the first major American school system to do so — The resolution followed pres

applicationstechmeme

The MediaSpin Dataset: Post-Publication News Headline Edits Annotated for Media Bias

arXiv:2412.02271v4 Announce Type: replace Abstract: We present MediaSpin, a large-scale language resource capturing how major news outlets modify headlines after publication, and MediaSpin-in-the-Wild

The new word in home construction could be “plastics”

Single-use plastics are a persistent source of environmental pollution, and the need to house a growing global population puts increasing pressure on resources such as timber. MIT engineers have an id

researchmit-tech-review