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arXiv:1805.11546v3 Announce Type: replace-cross Abstract: We examine the benefits of visual context in training neural language models to perform next-word prediction. A multi-modal neural architectur

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Not Forgotten: Implementation and Evaluation of a Personalized Episodic Memory for the Humanoid Robot Head Kim

DGX agent

arXiv:2607.24190v1 Announce Type: cross Abstract: Social robots that rely on large language models for conversation are unable to retain information across sessions. This absence of memory violates so

researcharxiv-cs-ai

28 Jul 2026

Nova3D: Code-Native Generation of Programmable 3D Assets

arXiv:2607.22738v1 Announce Type: cross Abstract: Current 3D generative models mostly produce a final surface: a visually strong but largely opaque mesh. Interactive 3D worlds need more than a surface

ObsDriveBench: Benchmarking Multimodal Understanding under Adverse Weather with Observability Awareness

arXiv:2607.23537v1 Announce Type: new Abstract: Autonomous driving under adverse weather remains a critical challenge, yet existing vision-language benchmarks mainly evaluate under standard conditions

PANOPTICON: A PII-Based Assemblage of Naturalistic Output Tokens for Investigating Privacy Leakage Within LLM Context Window

arXiv:2607.22695v1 Announce Type: new Abstract: Large Language Models (LLMs) are capable of generalizing human language for the completion of never-before-seen tasks, leading to widespread deployment.

Scale Weight Decay and Train Better

arXiv:2607.23777v1 Announce Type: cross Abstract: The discovery of scaling laws has motivated training neural networks on ever increasing quantities of data. This is typically done with a constant dec

Seesaw: Accelerating Training by Balancing Learning Rate and Batch Size Scheduling

arXiv:2510.14717v2 Announce Type: replace-cross Abstract: Increasing the batch size during training -- a ''batch ramp'' -- is a promising strategy to accelerate large language model pretraining. While

Spatial Reasoning in LLM Game Agents: Impact of Causal Context and Multi-Step Planning

arXiv:2607.22732v1 Announce Type: new Abstract: LLM-based game agents often perform poorly on more complex tasks. This work examines whether these failures are linked to limited spatial reasoning and

StanceFlip: A Comprehensive Multi-Dimensional Benchmark for Multimodal Conversational Stance Flipping Forecasting

arXiv:2607.24191v1 Announce Type: cross Abstract: Conversational stance detection has shifted from static text analysis to dynamic multimodal modeling. However, existing benchmarks exhibit three key l

SWE-rebench Multilingual Update (Go, Java, Python, Rust, TS). Evaluated: GLM-5.2, DeepSeek-V4 Pro, Qwen3.6-27B and others

model-releasesr-localllama

Hi everyone! We’ve just released a major update to the leaderboard! We are expanding beyond Python with a new multilingual slice featuring real-world software engineering tasks across 5 languages. Ope

Tailored untruths: How personalisation challenges LLM safeguards

arXiv:2510.12993v3 Announce Type: replace Abstract: Large Language Models (LLMs) can generate highly persuasive disinformation, yet little is known about how effectively they personalise it across lan

safetyarxiv-cs-cl

The Physics of Multi-Turn Long-Horizon Planning: From Pre-training to Post-training via Single- and Multi-Teacher On-Policy Agentic Distillation

arXiv:2607.24720v1 Announce Type: cross Abstract: Multi-turn long-horizon planning is critical for foundation model agents, yet how to fundamentally improve it remains unclear. Existing models are tra

safetyarxiv-cs-ai

Verbalized Particle Posterior: Bayesian Inference over Natural Language Hypotheses

arXiv:2607.22961v1 Announce Type: cross Abstract: Verbalized Machine Learning (VML) parameterizes a model as a natural-language prompt that an LLM evaluates as f(x; theta). The framework is interpreta

When LLM Defenses Backfire: Characterizing Safety, Performance, and Cost Trade-offs

arXiv:2607.24392v1 Announce Type: cross Abstract: Jailbreak defenses are essential for protecting large language models (LLMs), but they can also introduce secondary costs that weaken model utility. W

WISERouter: LLM Routing with Workload Budget Constraint

arXiv:2607.23765v1 Announce Type: cross Abstract: Large language models (LLMs) achieve impressive performance across multiple domains, but using the most capable model for every query is prohibitive a

researcharxiv-cs-ai

b10153

model-releasesllama-cpp-releases

model: Add support for Nanbeige4.2 (#25994) support nanbeige4.2 model fix fix flake8 Lint check fix loop bound check and drop redundant head_dim Co-authored-by: root lizongqiang@kanzhun.com Website: h

DM3D: Dynamic Mamba via Offset-Guided Feature Resampling for Point Cloud Understanding

arXiv:2512.03424v4 Announce Type: replace Abstract: State Space Models (SSMs) model long token sequences of point cloud with linear complexity, but require an unordered point cloud to be serialized. E

Language-Aware Distillation for Multilingual Instruction-Following Speech LLMs with ASR-Only Supervision

arXiv:2603.07025v2 Announce Type: replace Abstract: Speech Large Language Models (LLMs) that understand and follow instructions in many languages are useful for real-world interaction, but are difficu

LMEB: Long-horizon Memory Embedding Benchmark

arXiv:2603.12572v5 Announce Type: replace Abstract: Memory embeddings are crucial for memory-augmented systems, such as OpenClaw, but their evaluation is underexplored in current text embedding benchm

Offline Vision-Language Navigation with Geometric Goal Localization for Outdoor Environments

model-releasesarxiv-cs-ro

arXiv:2607.22226v1 Announce Type: new Abstract: Foundation-model-based vision-language navigation (VLN) has advanced autonomous robot navigation by enabling robots to interpret natural-language instru

Optimization of time-consuming experimental conditions using pseudo-experimental data guided by adaptive polynomial regression

arXiv:2607.22238v1 Announce Type: new Abstract: Bayesian optimization (BO) is an optimization method that sequentially proposes the next candidate explainable variables for optimizing target variables

RadSight: Towards Perceptually Reliable Multimodal Radiology Image Understanding

arXiv:2607.22293v1 Announce Type: new Abstract: Medical multimodal large language models (MLLMs) are increasingly expected to perform complex image understanding tasks, yet their reliability is often

Scaling Laws for Classical Machine Learning on Tabular Data: A Benchmark Study

arXiv:2607.21866v1 Announce Type: new Abstract: Prior classical-ML learning-curve work fits power laws to tree, linear, and kernel models on tabular data, but at small scale: typically one curve, one

Twins: Learn to Predict Unified Representations with Focal Loss

arXiv:2607.22531v1 Announce Type: new Abstract: Unified multimodal models seek a shared visual token space that supports both multimodal understanding and image generation. Discrete methods unify the

safetyarxiv-cs-cv

Unbiased Open World Regularization for Fair Self-Supervised Learning

arXiv:2607.22149v1 Announce Type: new Abstract: Despite recent advances, self-supervised learning (SSL) models and Joint-Embedding Predictive Architectures (JEPAs) remain susceptible to learning spuri

Local Ai

ai-sage/GigaChat3.1-Audio-10B-A1.8B · Hugging Face

GigaChat Audio 10B is an audio-native LLM built on top of the GigaChat 3.1 Lightning text model. A Conformer speech encoder and a modality adapter feed audio embeddings directly into a Mixture-of-Expe

local-air-localllama

26 Jul 2026

This part is spot on: > 'Overall, we found that we were over-constraining Claude Code...while these constraints were once needed to avoid wo…

model-releasesjerry-liu--x

This part is spot on: > 'Overall, we found that we were over-constraining Claude Code...while these constraints were once needed to avoid worst case scenarios, we have since found we can delete many o

26 Jul 2026

Deepseek V4 flash - Hy3 or is Qwen3.6 27B still the most solid for agentic/coding?

model-releasesr-localllama

I understand that the laguna model is either still buggy or potentially benchmaxxed. So I’d like to know for people who really tested, are DS flash or Hy3 really better in your usecase? submitted by /

25 Jul 2026

Kimi Linear 48B A3B?

model-releasesr-localllama

Just noticed this exists, 1M context MOE with 48B par seems just like what Ive been looking for - it runs pretty damn fast too compared to Qwen 3.6 35B. after some testing it seems capable of producin

25 Jul 2026

AI-Driven Surrogate Models for Predicting Electrode-Scale Discharge Behavior in Lithium-Ion Batteries

arXiv:2607.20577v1 Announce Type: new Abstract: Physics-based simulations are essential for understanding the electrode-scale discharge behavior of lithium-ion batteries (LIBs) but suffer from prohibi

researcharxiv-cs-lg

Are Single-Token Sparse Autoencoder Features Causally Necessary? Layer-Depth and SAE-Family Effects

arXiv:2607.20596v1 Announce Type: cross Abstract: Sparse autoencoder (SAE) features are used to interpret and steer large language models, yet whether a feature's causal role is stable across SAE fami

DataPrep-Bench: Benchmarking LLMs as Training Data Preparators

arXiv:2607.20465v1 Announce Type: cross Abstract: The quality of training data fundamentally determines the capabilities of large language models (LLMs), yet no unified benchmark exists to measure how

Efficient and Interpretable Body-Based Emotion Recognition with Lightweight Temporal Convolutional Networks

arXiv:2607.20820v1 Announce Type: new Abstract: Body-based emotion recognition is important for real-time affective systems, but graph-based skeleton models can be computationally expensive. This pape

Lessons and Open Questions from a Unified Study of Camera-Trap Species Recognition Over Time

arXiv:2603.20509v2 Announce Type: replace Abstract: Camera traps are vital for large-scale biodiversity monitoring, yet accurate automated analysis remains challenging due to diverse deployment enviro

Memoir: Should a Model Write to Its Memory While It Thinks?

arXiv:2607.20792v1 Announce Type: new Abstract: Memoir combines per-sample fast memory, shared slow parameters, variable-depth latent recurrence, and a future-latent energy objective. We test its risk

researcharxiv-cs-lg

NVIDIA, Palantir, Replit, Microsoft, Crowdstrike, Dell and others send a strong message to congress to keep open access to open weights mode…

NVIDIA, Palantir, Replit, Microsoft, Crowdstrike, Dell and others send a strong message to congress to keep open access to open weights models. 'Our AI leadership will be judged not by one frontier AI

safetyyann-lecun--x

Post-Hoc Reasoning in Chain of Thought: Decoding and Steering Pre-Committed Answers

arXiv:2603.01437v2 Announce Type: replace Abstract: As chain of thought (CoT) has become central to scaling reasoning capabilities in large language models (LLMs), it has also emerged as a promising t

researcharxiv-cs-ai

Scaling Closed-Loop Feature Channel Configuration with LLMs

arXiv:2607.20516v1 Announce Type: cross Abstract: Promising initial results in closed-loop large-language-model-based channel-configuration search demonstrated that neural-network widths can be optimi

Show, Don't Tell: Evaluating Spatial Cognition in Generative Pixels Rather Than LLM Text

arXiv:2607.21072v1 Announce Type: new Abstract: Spatial intelligence is essential for agents to move from static semantic understanding toward interacting with the physical world. Many spatial tasks a

The Storyteller in the Model: Narrative Pattern Inheritance, Escalation Dynamics, and Alignment Governance in LLMs

arXiv:2607.20449v1 Announce Type: cross Abstract: LLMs are trained predominantly on human-authored text, yet the structural and narrative conventions embedded in that text are rarely examined as a sou

safetyarxiv-cs-ai

Associative Emotional Learning in Convolutional Neural Networks

arXiv:2607.19327v2 Announce Type: replace Abstract: Associative emotional learning enables organisms to adaptively link pleasant or unpleasant outcomes to the presence of predictive stimuli. Whereas c

researcharxiv-cs-ai

Local Ai

Brewing Stronger Features: Dual-Teacher Distillation for Multispectral Earth Observation

arXiv:2602.19863v3 Announce Type: replace Abstract: Foundation models are transforming Earth Observation (EO), yet the diversity of EO sensors and modalities makes a single universal model unrealistic

local-aiarxiv-cs-cv

Cumsum-Composable Phase Transport for Low-Cost Streaming Keyword Spotting

arXiv:2607.20086v1 Announce Type: cross Abstract: State-space sequence models are attractive for streaming speech because they maintain compact recurrent state, but scan-style training kernels can hav

Fine-grained Computation-Communication Overlap via Tile-level Signaling and Scheduling for Mixture-of-Experts

arXiv:2607.19539v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) architectures increase model capacity without proportionally increasing computation cost and have become a key building block

GH-ESD: Grounded Hypothesis-Driven Error Slice Discovery for Instance-Level Vision Tasks

arXiv:2512.24592v3 Announce Type: replace Abstract: Systematic failures of vision models on semantically coherent subsets, known as error slices, reveal limitations in robustness and evaluation. Exist

Group-of-Latents: Perceptual Video Compression at Extreme Bitrates via Masked Latent Generative Modeling

arXiv:2607.19437v1 Announce Type: cross Abstract: Most existing video compression algorithms follow a paradigm of transformation and quantization, optimizing the trade-off between distortion and bitra

researcharxiv-cs-cv

How Fast Can Reward Models Score? A Systems Study of C++ and PyTorch Inference Runtimes for RLHF

arXiv:2607.19712v1 Announce Type: new Abstract: In RLHF pipelines, reward scoring blocks policy updates. Slow scoring bottlenecks the entire loop, since no update runs until every rollout gets a score

safetyarxiv-cs-lg

MagicPrompt: Ultra-Lightweight Prompt Tuning for Video Generation

arXiv:2607.14595v2 Announce Type: replace Abstract: Large-scale video diffusion models deliver strong generation performance, but full fine-tuning for downstream tasks incurs prohibitive computational