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Hallucination Is Linearly Decodable from Mid-Layer Hidden States in Quantized LLMs

arXiv:2606.02628v1 Announce Type: cross Abstract: We investigate whether open-source LLMs encode a linearly separable truthfulness signal in their hidden states, and at which network depth this signal

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Hallucinations as Orthogonal Noise: Inference-Time Manifold Alignment via Dynamic Contextual Orthogonalization

DGX agent

arXiv:2606.03022v1 Announce Type: cross Abstract: Hallucination in Large Language Models (LLMs), characterized by the generation of content inconsistent with contextual facts or logical constraints --

model-releasesarxiv-cs-ai

3 Jun 2026

Hedge-Bench: Benchmarking Agents on Hard, Realistic Tasks Pertaining to Financial Reasoning

arXiv:2606.03918v1 Announce Type: new Abstract: AI agents can increasingly handle the mechanical tasks of financial analysis: retrieving documents, calculating formulas, updating spreadsheets. The har

Honesty in Causal Forests: When It Helps and When It Hurts

arXiv:2506.13107v4 Announce Type: replace Abstract: Causal forests estimate how treatment effects vary across individuals, guiding personalized interventions in areas like marketing, operations, and p

how does the brain build and track an internal state of the world from (possibly incomplete and noisy) visual observations? i believe visual…

model-releasesyann-lecun--x

how does the brain build and track an internal state of the world from (possibly incomplete and noisy) visual observations? i believe visual state tracking will be the grand challenge for vision in th

How Many Trees in a Random Forest? A Revisited Approach with Plateau Search and Optuna Integration

arXiv:2606.03549v1 Announce Type: new Abstract: Hyperparameter optimization (HPO) for Random Forest faces a specific difficulty in tuning the number of trees: the predictive score typically improves m

How Quantization Changes Interpretable Features: A Sparse Autoencoder Analysis of Language Models

arXiv:2606.03002v1 Announce Type: cross Abstract: Quantization is a standard path to deploying large language models, and a quantized model is typically judged acceptable when its perplexity or downst

How Wasmer used Codex to build a Node.js runtime for the edge

Wasmer leveraged OpenAI's Codex to develop a Node.js runtime optimized for edge computing environments. The project demonstrates how AI-assisted code generation can accelerate the creation of speciali

model-releasesopenai

Hybrid Dynamics Modeling for a Flexible 2-DoF Robotic Arm

model-releasesarxiv-cs-ro

arXiv:2606.02969v1 Announce Type: new Abstract: This paper examines three approaches for modeling the dynamics of a flexible-link 2-DoF robotic arm to address unmodeled dynamics not captured by rigid-

HyperPatch: Sequential Knowledge Editing Under n-ary Structural Drift

arXiv:2606.03179v1 Announce Type: new Abstract: Large Language Models (LLMs) rely on Knowledge Editing (KE) to maintain temporal validity, yet real-world knowledge is inherently n-ary. We demonstrate

I like the racing and Stardew Valley portions, the conclusion is very Claude, though.

model-releasesethan-mollick--x

This appears to be Ethan Mollick's personal reflection on an AI-generated or AI-assisted project that includes racing and Stardew Valley game elements, with commentary that the conclusion exhibits cha

I present to you... The Spaghetti Benchmark

'Will Smith eating spaghetti' became a shorthand for early-stage AI video generation limitations , with the original 2023 clip generated with ModelScope showing distorted faces, morphed hands, and unn

model-releasesr-chatgpt

Identifying Quantum Structure in AI Language: Evidence for Evolutionary Convergence of Human and Artificial Cognition

arXiv:2511.21731v2 Announce Type: replace-cross Abstract: We present the results of cognitive tests on conceptual combinations, performed using specific Large Language Models (LLMs) as test subjects.

IdiomX A Multilingual Benchmark for Idiom Understanding, Retrieval, and Interpretation

arXiv:2606.02584v1 Announce Type: cross Abstract: Idiomatic expressions remain a persistent challenge for natural language processing because their meanings are often non-compositional, context-depend

If this prompt feels well written to you, it's because Suzanne is a writer in her little spare time! You can read her short story, Mall of A…

If this prompt feels well written to you, it's because Suzanne is a writer in her little spare time! You can read her short story, Mall of America here: https://suzannewang.com/mall-of-america It's on

model-releasesthariq--x

Improvise, Adapt, Overcome: An On-The-Fly Multifidelity Algorithm for Efficient Machine Learning

arXiv:2606.02662v1 Announce Type: cross Abstract: Machine learning has accelerated quantum chemistry but is hindered by the prohibitive cost of generating high fidelity training data. Multifidelity ma

In early May, the best superforecasters predicted that, by the end of the year, the longest METR 80% task horizons would reach 3-4 hours. In…

model-releasesethan-mollick--x

In early May, the best superforecasters predicted that, by the end of the year, the longest METR 80% task horizons would reach 3-4 hours. In late May, Claude Mythos achieved that number. We also asked

InftyThink+: Effective and Efficient Infinite-Horizon Reasoning via Reinforcement Learning

arXiv:2602.06960v3 Announce Type: replace-cross Abstract: Large reasoning models achieve strong performance by scaling inference-time chain-of-thought, but this paradigm suffers from quadratic cost, c

Instant Personalized Large Language Model Adaptation via Hypernetwork

arXiv:2510.16282v2 Announce Type: replace Abstract: Personalized large language models (LLMs) tailor content to individual preferences using user profiles or histories. However, existing parameter-eff

Introducing new capabilities to GPT-Rosalind

GPT-Rosalind is an OpenAI model with newly introduced capabilities designed to enhance its performance in specific tasks or domains. The update likely expands the model's functionality in areas such a

model-releasesopenai

Investigating Adversarial Robustness of Multi-modal Large Language Models

arXiv:2606.03713v1 Announce Type: new Abstract: Multi-modal Large Language Models (MLLMs) achieve strong performance on vision-language tasks, but incorporating visual inputs through a vision encoder

JAVEDIT: Joint Audio-Visual Instruction-Guided Video Editing with Agentic Data Curation

arXiv:2606.03168v1 Announce Type: new Abstract: While instruction-based video editing has seen significant progress, joint audio-visual editing remains constrained by the absence of dedicated datasets

Jerry Liu built one of the most installed pieces of AI plumbing of the last three years. Then he sat down and told me the framework era he h…

model-releasesjerry-liu--x

Jerry Liu built one of the most installed pieces of AI plumbing of the last three years. Then he sat down and told me the framework era he helped create is over. The agent harness ate the abstraction

KForge: LLM-Driven Cross-Platform Kernel Generation for AI Accelerators

arXiv:2606.02963v1 Announce Type: new Abstract: Production inference increasingly targets a heterogeneous mix of accelerators. Agentic pipelines interleave reasoning, tool calls, and multi-agent coord

Knowledge Editing in Masked Diffusion Language Models

arXiv:2606.03924v1 Announce Type: new Abstract: Knowledge editing aims to update or correct factual knowledge in a language model. A widely used approach, locate-then-edit, does this in two steps: it

Knowledge-Preserved Model Tuning in Null-Space for Robust Spatio-Temporal Video Grounding

arXiv:2606.03539v1 Announce Type: new Abstract: Spatio-Temporal Video Grounding aims to localize object tubes based on textual queries. While recent methods have achieved remarkable success, they main

LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolation

arXiv:2510.22491v3 Announce Type: replace-cross Abstract: Generating high-fidelity 3D geometries under explicit parameter constraints is central to engineering design, yet current methods often requir

Language Bias under Conflicting Information in Multilingual LLMs

arXiv:2604.07123v2 Announce Type: replace Abstract: Large Language Models (LLMs) have been shown to contain biases in the process of integrating conflicting information when answering questions. Here

Laplacian Representations for Decision-Time Planning

arXiv:2602.05031v2 Announce Type: replace Abstract: Planning with a learned model remains a key challenge in model-based reinforcement learning (RL). In decision-time planning, state representations a

LEAP: Supercharging LLMs for Formal Mathematics with Agentic Frameworks

arXiv:2606.03303v1 Announce Type: new Abstract: Large Language Models (LLMs) exhibit strong informal mathematical reasoning but struggle to generate mechanically verifiable proofs in formal languages

Learning Temporal Causal Structure via Smooth Differentiable Optimization

arXiv:2606.03227v1 Announce Type: new Abstract: Causal discovery with instantaneous effects in multivariate time series is challenging, as the instantaneous structure must be acyclic. Prior methods en

Leave it to the Specialist: Repair Sparse LLMs with Sparse Fine-Tuning via Sparsity Evolution

arXiv:2505.24037v3 Announce Type: replace Abstract: Sparse large language models (LLMs) offer an attractive direction toward efficient deployment, but adapting them to downstream tasks remains challen

Let the Dynamics Flow: Stable Flow Matching Dynamical Systems

model-releasesarxiv-cs-ro

arXiv:2606.03834v1 Announce Type: new Abstract: Flow matching has recently emerged as a powerful approach for imitation learning, enabling scalable, expressive, and multimodal motion policies. However

LiveBand: Live Accompaniment Generation in the Audio Domain

arXiv:2606.03803v1 Announce Type: cross Abstract: We present LiveBand, a real-time system that generates high-fidelity music accompaniments to live audio input, respecting strict causal constraints. O

Locality Does Not Imply Reachability: Boundary Repair in Block-Sparse Causal Attention

arXiv:2606.02680v1 Announce Type: new Abstract: Sparse causal attention is usually described by sequence locality: nearby tokens should remain easy to access, while distant tokens may be dropped to re

Low-Frequency Shortcuts in Texture-Driven Visual Learning

arXiv:2606.03493v1 Announce Type: new Abstract: Neural networks suffer from shortcut learning, where learned features generalize well to the training set but not to in-distribution (ID) or out-of-dist

Make sure to update your runtime first! > lms runtime update --all Learn more about this model release https://x.com/googlegemma/status/2062…

model-releaseslm-studio--x

Make sure to update your runtime first! > lms runtime update --all Learn more about this model release https://x.com/googlegemma/status/2062202706882883696?s=20 Meet Gemma 4 12B! A unified, encoder-fr

MARIO: Motion-Augmented Real-Time Multi-Sensor Inertial Odometry

arXiv:2606.02996v1 Announce Type: cross Abstract: Inertial odometry (IO) using only Inertial Measurement Units (IMUs) provides a lightweight solution for human motion tracking in augmented reality (AR

MedCUA-Bench: A Screenshot-Only Benchmark for Clinical Computer-Use Agents

arXiv:2606.03203v1 Announce Type: new Abstract: Computer-use agents could automate repetitive screen-based clinical work, but their reliability in medical graphical user interfaces remains largely unv

MemoGen: Can Past Experience Improve Future Text-to-Image Generation?

arXiv:2606.03243v1 Announce Type: new Abstract: Modern text-to-image models have achieved strong visual synthesis, yet remain unreliable when prompts require implicit visual constraints, relational re

Message Tuning Outshines Graph Prompt Tuning: A Prismatic Space Perspective

arXiv:2606.03290v1 Announce Type: cross Abstract: Graph Foundation Models (GFMs), built upon the Pre-training and Adaptation paradigm, have emerged as a research hotspot in graph learning. For GNN-bas

MiniMax M3 arrives with MiniMax Sparse Attention (MSA), 15.6x faster decoding at 1M tokens. We're partnering with @MiniMax_AI to power the i…

model-releasesfireworks-ai--x

MiniMax M3 arrives with MiniMax Sparse Attention (MSA), 15.6x faster decoding at 1M tokens. We're partnering with @MiniMax_AI to power the inference behind this week's launch. Head to http://minimax.i

Mixed-Modality Dual Face-Hair Retrieval

arXiv:2606.03470v1 Announce Type: new Abstract: We introduce Dual Face-Hair Retrieval (DFHR), a new mixed-modality dual-reference task in image retrieval where a query consists of a face image specify

MLSkip: Data Skipping for ML Filters via Lightweight Metadata

arXiv:2606.03946v1 Announce Type: cross Abstract: Database vendors recently released AI functions that can be used in filter predicates. As such functions often rely on costly, black-box ML models, th

Multi-Modal Machine Learning for Breast Cancer Recurrence Prediction

arXiv:2606.02892v1 Announce Type: new Abstract: Breast cancer recurrence, a leading cause of long-term mortality among survivors, requires timely and accurate risk assessment to guide follow-up care a

Multi^2: Hierarchical Multi-Agent Decision-Making with LLM-Based Agents in Interactive Environments

arXiv:2606.03698v1 Announce Type: new Abstract: A central goal of large language model (LLM) research is to build agentic systems that can plan, act, and adapt through sustained interaction with dynam

Multilingual Unlearning in LLMs: Transfer, Dynamics, and Reversibility

arXiv:2606.03291v1 Announce Type: new Abstract: Large language models (LLMs) can memorize sensitive facts, motivating unlearning methods that remove targeted knowledge without costly retraining. Howev

MultiTurnPSB: Evaluating Multi-Turn Jailbreak Attacks an dClassifier-Based Defenses for Medical AI Safety

arXiv:2606.02630v1 Announce Type: cross Abstract: Patient-facing medical chatbots are commonly evaluated on single-turn prompts, yet real users push back after refusals, add urgency, and invoke author