Search: “model-releases”

My timeline seems to have people surprised that U Chicago is getting Claude, but tons of schools (including U Penn where I teach) have schoo…

model-releasesethan-mollick--x

My timeline seems to have people surprised that U Chicago is getting Claude, but tons of schools (including U Penn where I teach) have school-wide AI There are lots of things that need to be figured o

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Neural Navigation Functions for Zero-Shot Generalizable Motion Planning

arXiv:2606.03756v1 Announce Type: cross Abstract: We introduce Neural Navigation Functions (Neural-NF), a learned reactive navigation function capable of zero-shot transfer across unseen environment g

NeuroArmor: Safe-Variant-Guided Representation Consistency for Selective Re-Anchoring in Jailbreak Defense

arXiv:2606.03486v1 Announce Type: cross Abstract: Large language models remain vulnerable to jailbreak attacks that hide harmful intent behind seemingly ordinary requests such as role-play, translatio

Neutrino Fingerprints: Image-Based Encodings of IceCube Events for CNN Direction Reconstruction

arXiv:2606.02788v1 Announce Type: cross Abstract: Reconstructing the direction of incoming neutrinos in the IceCube Neutrino Observatory is an important problem in astrophysics. The public IceCube--Ne

OpenAI ran a hiring challenge, but the top candidate was one they couldn’t hire: our autonomous research agent, Aiden. In Parameter Golf, Ai…

model-releasesclem-delangue--x

OpenAI ran a hiring challenge, but the top candidate was one they couldn’t hire: our autonomous research agent, Aiden. In Parameter Golf, Aiden ran for 22 days, and out-outperformed all 1,016 other re

OpenEAI-Platform: An Open-source Embodied Artificial Intelligence Hardware-Software Unified Platform

arXiv:2606.03392v1 Announce Type: new Abstract: Embodied AI in the real world requires both accurate hardware and robust vision-language-action (VLA) policies. We present OpenEAI-Platform, a fully ope

Optimal Initialization in Depth: Lyapunov Initialization and Limit Theorems for Deep Leaky ReLU Networks

arXiv:2602.10949v2 Announce Type: replace-cross Abstract: Effective initialization in deep networks requires an understanding of random neural networks. In this work, a rigorous probabilistic analysis

Optimizing Explicit Unit-Distance Lower-Bound Certificates

arXiv:2606.03419v1 Announce Type: cross Abstract: The 2026 disproof of Erdos's unit-distance conjecture and Sawin's subsequent explicit quantitative refinement show that the maximum number u(n) of uni

Outsmarting the Chameleon: Counterfactual Decoupling for Tactical OOD Shifts in Live Streaming Risk Assessment

arXiv:2606.02946v1 Announce Type: new Abstract: Live streaming has emerged as a primary medium for social interaction and digital commerce, yet it is increasingly plagued by sophisticated risks. A fun

OVO-S-Bench: A Hierarchical Benchmark for Streaming Spatial Intelligence in Multimodal LLMs

arXiv:2606.03890v1 Announce Type: new Abstract: Multimodal agents in robotics, AR, and autonomous driving must reason about places and layouts from continuous egocentric streams, often using evidence

PatchScene: Patch-based Voxel Diffusion for Large-Scale Scene Completion

arXiv:2606.03915v1 Announce Type: new Abstract: We propose PatchScene, a novel diffusion-based framework for large-scale LiDAR scene completion. Unlike existing methods that rely on global latent repr

Perceive Before Reasoning: A Pre-Reasoning Perception Framework for Efficient and Reliable Proactive Mobile Agents

arXiv:2606.03236v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have substantially advanced mobile agents, yet proactive mobile assistance remains challenging because agents m

PerchRL: Vision-Based Agile Perching on Inclined Platforms under Rapid and Irregular Motion

arXiv:2606.03441v1 Announce Type: cross Abstract: Autonomous vision-based perching of quadrotors on moving inclined platforms is critical for air-ground collaboration but remains challenging due to th

PieArena: Ranking and Profiling Language Agents in Realistic Negotiation Scenarios

arXiv:2602.05302v3 Announce Type: replace Abstract: We present an in-depth evaluation of LLMs' ability to negotiate, a central business task requiring strategic reasoning, theory of mind, and economic

PINNfluence: Interpreting PINNs through Influence Functions

arXiv:2409.08958v3 Announce Type: replace-cross Abstract: Physics-informed neural networks (PINNs) have emerged as a powerful deep learning approach for solving partial differential equations (PDEs) i

Plan, Verify and Fill: A Structured Parallel Decoding Approach for Diffusion Language Models

arXiv:2601.12247v3 Announce Type: replace-cross Abstract: Diffusion Language Models (DLMs) present a promising non-sequential paradigm for text generation, distinct from standard autoregressive (AR) a

Plan2Map: A Multimodal Benchmark for Document-Grounded Geospatial Boundary Reconstruction from Planning Records

arXiv:2606.02747v1 Announce Type: cross Abstract: Planning records define restrictions over geographic areas, but their source documents often provide only indirect spatial evidence rather than machin

Pretraining Language Models on Historical Text

arXiv:2606.02991v1 Announce Type: cross Abstract: We introduce TypewriterLM, a 7.24B History language model (LM) trained exclusively on English text predating 1913. Developing History LMs requires add

Proof-Refactor: Refactoring Generated Formal Proofs into Modular Artifacts

arXiv:2606.03743v1 Announce Type: new Abstract: While Large Language Models (LLMs) have shown strong performance in generating formal proofs, their outputs often remain less readable, modular, maintai

ProtocolBench: Which LLM MultiAgent Protocol to Choose?

arXiv:2510.17149v3 Announce Type: replace Abstract: As large-scale multi-agent systems evolve, the communication protocol layer has become a critical yet under-evaluated factor shaping performance and

Psi-Bench: Evaluating Persona-Sensitive Influencing in Persuasive Dialogues

arXiv:2606.02754v1 Announce Type: new Abstract: Personalization is a crucial capability of modern language agents. However, current research primarily positions personalized agents as passive responde

PubTables-v2: A new large-scale dataset for full-page and multi-page table extraction

arXiv:2512.10888v3 Announce Type: replace Abstract: Table extraction (TE) is a key challenge in document understanding. Traditional approaches detect tables first, then recognize their structure. Rece

PyraMathBench: Evaluating and Improving Mathematical Capability in Large Language Models

arXiv:2606.03858v1 Announce Type: new Abstract: Despite the pivotal role of numerical reasoning as the cornerstone of mathematical capabilities in large language models (LLMs) across applications, few

q0: Primitives for Hyper-Epoch Pretraining

arXiv:2606.03938v1 Announce Type: cross Abstract: Multi-epoch training is becoming the standard now that compute is growing faster than the supply of high-quality text. But pretraining a single model

Qift: Shift-Friendly No-Zero W2 Post-Training Quantization for Rotated W2A4/KV4 LLM Inference

arXiv:2606.02823v1 Announce Type: new Abstract: Two-bit weight quantization is attractive for memory-efficient LLM inference, but the standard W2 level set {-2,-1,0,+1} often collapses under aggressiv

Quadratic integrate-and-fire neurons exhibit less fragmented loss landscapes and outperform leaky integrate-and-fire neurons in spike-based gradient descent

arXiv:2606.03935v1 Announce Type: cross Abstract: The ability to train spiking neural networks is essential for modeling biological neural networks as well as for neuromorphic computing. However, for

QUIVER: Quantum-Informed Views for Enhanced Representations in Large ML Models

arXiv:2606.02785v1 Announce Type: new Abstract: Large machine learning models benefit substantially from multimodal inputs that provide a complementary view of the same example. We introduce QUIVER (Q

Qwen-Image-Flash: Beyond Objective Design

arXiv:2606.03746v1 Announce Type: cross Abstract: Few-step distillation has become an effective strategy for accelerating advanced visual generative models, yet prior work has largely focused on disti

RadarSFD: Single-Frame Diffusion with Pretrained Priors for Radar Point Clouds

arXiv:2509.18068v2 Announce Type: replace Abstract: Millimeter-wave radar provides robust perception in fog, smoke, dust, and low light, making it attractive for size-, weight-, and power-constrained

Re-Ranking Through an Attribution Lens for Citation Quality in Legal QA

arXiv:2606.03728v1 Announce Type: new Abstract: Retrieval-augmented generation systems for legal question answering typically retrieve passages based on semantic similarity and provide them to a langu

RealClawBench: Live OpenClaw Benchmarks from Real Developer-Agent Sessions

arXiv:2606.03889v1 Announce Type: new Abstract: Agent benchmarks should reflect what users actually ask deployed agents to do, yet existing benchmarks often miss key realism properties of real develop

ReaLM: Residual Quantization Bridging Knowledge Graph Embeddings and Large Language Models

arXiv:2510.09711v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have recently emerged as a powerful paradigm for Knowledge Graph Completion (KGC), offering strong reasoning and

Reasoning Structure of Large Language Models

arXiv:2606.03883v1 Announce Type: new Abstract: Large reasoning models (LRMs) are often evaluated using metrics such as final-answer accuracy or token count. However, identical scores on these metrics

Reconstructing Objects along Hand Interaction Timelines in Egocentric Video

arXiv:2512.07394v2 Announce Type: replace Abstract: We introduce the task of Reconstructing Objects along Hand Interaction Timelines (ROHIT). We first define the Hand Interaction Timeline (HIT) from a

Relational Linearity is a Predictor of Hallucinations

arXiv:2601.11429v2 Announce Type: replace-cross Abstract: Hallucination is a central failure mode of language models (LMs). We focus on hallucinations in response to questions like: 'Which instrument

Reliability-Guided Depth Fusion for Glare-Resilient Navigation Costmaps

arXiv:2606.03421v1 Announce Type: new Abstract: Specular glare on reflective floors, glass boundaries, and glossy indoor surfaces frequently corrupts active-stereo RGB-D depth measurements, producing

RESCAST-100K: A Comprehensive Dataset for Cross-Domain Residential Load and Indoor Temperature Forecasting

arXiv:2606.02852v1 Announce Type: new Abstract: Accurate short-term forecasting of residential energy load and indoor temperature is essential for home energy management systems, grid-level demand res

Rethinking Molecular Text Representations for LLMs: An Empirical Study

arXiv:2606.03057v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used for molecular tasks, but it remains unclear which molecular representation to use. We present a sys

Revisiting Embodied Chain-of-Thought for Generalizable Robot Manipulation

arXiv:2606.03784v1 Announce Type: new Abstract: Embodied chain-of-thought (CoT) aims to bridge linguistic reasoning and robotic control, but its effective form and integration strategy remain underexp

RobotValues: Evaluating Household Robots When Human Values Conflict

arXiv:2606.03312v1 Announce Type: cross Abstract: While household robots are often evaluated based on task completion, everyday domestic environments involve value-conflicting situations in which robo

ROBUST-WT: Robust Uncertainty-aware Segmentation Transform via Whitening and Training Enhancements

arXiv:2606.03069v1 Announce Type: cross Abstract: Generalized segmentation of medical images prevents performance degradation when different imaging devices and clinical protocols are used across mult

RogueMerge: Robust and Unified Attacks against LLM Model Merging

arXiv:2606.03344v1 Announce Type: cross Abstract: Model merging composes specialized capabilities into a single LLM by aggregating task vectors sourced from unverified public platforms, exposing a cri

Safety Measurements for Fine-tuned LLMs Should be Grounded in Capability

arXiv:2606.03648v1 Announce Type: cross Abstract: Adapting foundation large language models to a user's task or preferred style through fine-tuning can result in compromising the model's safety. Previ

SagaQA: A Multi-hop Reasoning Benchmark for Long-form Narrative Understanding in TV Series

arXiv:2606.03301v1 Announce Type: new Abstract: We introduce SagaQA, a long-form video benchmark for multi-hop reasoning over full-length TV series. Existing video reasoning benchmarks often emphasize

Sample-Size Scaling of the African Languages NLI Evaluation

arXiv:2606.03219v1 Announce Type: new Abstract: African languages have very little labelled data, and it is unclear if augmenting the quantity of annotation data reliably enhances downstream performan

Samudra 2: Scaling Ocean Emulators across Resolutions

arXiv:2606.02610v1 Announce Type: cross Abstract: Ocean general circulation models (OGCMs) are essential to climate science but computationally expensive, limiting ensemble size and forcing scenarios.

Scalable On-Hardware Training of Quantum Neural Networks and Application to Clinical Data Imputation

arXiv:2606.03517v1 Announce Type: cross Abstract: Training quantum neural networks (QNNs) on quantum hardware is currently bottlenecked by the cost of gradient estimation: standard parameter-shift met

SCOPE: Real-Time Natural Language Camera Agent at the Edge

arXiv:2606.02951v1 Announce Type: cross Abstract: Deploying language-driven agents in robotics requires evaluations that reflect real-world task demands: natural-language instructions with reproducibl