Search: “model-releases”

Self-Supervised Keyframe Discovery for Horizon-Invariant Behavior Cloning

arXiv:2610.10857v1 Announce Type: new Abstract: Behavior cloning (BC) in non-Markovian environments is a challenging problem because policies have to reason over contextual information over long horiz

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Model Releases

Sera: Semantic Representation Aggregation for Reliable and Interpretable Battery Health Forecasting

DGX agent

arXiv:2610.11567v1 Announce Type: cross Abstract: Battery state of health (SoH) forecasting is important for battery management, but remains challenging due to nonlinear degradation and heterogeneity

model-releasesarxiv-cs-ai

9 Oct 2026

SignRAG: Unified Retrieval-Augmented Gloss-Free Sign Language Translation

arXiv:2610.11371v1 Announce Type: new Abstract: Contemporary decoder-only large language models (LLMs) have demonstrated strong capabilities across a wide range of domains. However, existing pretraini

SlopSoup TV. A live, never-ending 24/7 pixel-art TV network inspired by old-school late night Adult Swim. No human makes any of it.

SlopSoup TV is a live, never-ending pixel-art TV network. Every script, character, voice, camera cut and schedule decision is made by models. It's made to be very absurd, dark and strange. Hardware: o

Smoothing the Top-k Exposure Boundary for Sparse Mixture-of-Experts

arXiv:2610.11575v1 Announce Type: new Abstract: Sparse Mixture-of-Experts models scale parameter capacity efficiently while maintaining a fixed compute budget per token. However, traditional training

SpaceCast-Bench: Evaluating Predictive Spatial Reasoning in Vision-Language Models

arXiv:2610.12402v1 Announce Type: cross Abstract: Existing spatial reasoning benchmarks mainly test spatial perception: reading off relations already visible in the input. Yet real-world spatial intel

SparseDecoding: Decoding-Aware Pruning for Accurate and Efficient LLM Inference

arXiv:2610.12327v1 Announce Type: cross Abstract: The memory-bound nature of the decoding stage of large language model (LLM) inference incurs significant latency. Layer-wise training-free network pru

Spectral Weight Decay: Inducing Low-Rank Structure in Neural Network Weights

arXiv:2610.11730v1 Announce Type: new Abstract: Standard weight decay treats each weight matrix as a vector and ignores its spectral structure. We introduce spectral weight decay, a post-step decouple

Spectrally Targeted Muon

arXiv:2610.10965v1 Announce Type: new Abstract: The Muon optimizer orthogonalizes each update matrix, setting all of its singular values to one, and has proven highly effective for training large lang

SPERA: Spherical Prior EEG Foundation Model with Geometry- and Frequency-Aware Latent Prediction

arXiv:2610.10571v1 Announce Type: new Abstract: Electroencephalography (EEG) provides a non-invasive measure of ongoing neural activity, but building general-purpose EEG models remains challenging due

SpikeSSL: A Universal Spike Inference Framework with Dynamics-Informed State-Space Layers

arXiv:2610.11456v1 Announce Type: new Abstract: Two-photon calcium imaging is a standard tool for recording large neural populations in vivo, yet inferring spikes accurately across the growing diversi

Stability-Plasticity Balance via Singular-Vector Selection in LLM Continual Learning

arXiv:2610.11076v1 Announce Type: cross Abstract: Domain-specific continual adaptation of LLMs risks catastrophic forgetting, creating a fundamental tension between acquiring new capabilities and pres

STAG: A Sparse Traversability-Aware Graph Representation from Grid-Based Costmaps for Robotic Navigation

model-releasesarxiv-cs-ro

arXiv:2610.11943v1 Announce Type: new Abstract: Autonomous rovers navigating large unstructured environments need efficient global planning that accounts for terrain traversability. However, searching

SteerablePlex: Can We Steer Full-Duplex Models?

arXiv:2610.12201v1 Announce Type: cross Abstract: Full-duplex speech models can listen and speak simultaneously, enabling natural interaction, but become increasingly difficult to control as the conve

Stepping away from Benchmarks and Code, what models are you using for Creating writing projects

All anyone ever talks in this sub is about x new model having x benchmark scores and how well it can code. Or some new tech to increase t/s for qwen. So I wanted to go back to the roots of this sub an

Stochastic Teacher Intervention for Agentic On-Policy Distillation

arXiv:2610.10878v1 Announce Type: cross Abstract: On-policy distillation (OPD) efficiently transfers capabilities from a stronger teacher to a student language model through dense token-level supervis

Stop My Dancing! Understanding, Detecting and Attributing Motion-Aware Deepfake Videos

arXiv:2610.11496v1 Announce Type: new Abstract: Pose-guided diffusion models can now synthesize entire human figures in motion, spawning a new class of deepfakes: Motion Aware Deepfake (MAD) that have

Stop Probing, Start Coding: Why Linear Probes and Sparse Autoencoders Fail at Compositional Generalisation

arXiv:2603.28744v2 Announce Type: replace Abstract: The linear representation hypothesis states that neural network activations encode high-level concepts as linear mixtures. However, under superposit

StoreBench: A Live-Commerce Environment for Evaluating and Training Autonomous Operator Agents

arXiv:2610.10942v1 Announce Type: new Abstract: Reinforcement learning environments are now a primary lever for improving large language model (LLM) capabilities in post-training, yet most agentic ben

Strategic Governance of AI Models in Earth Science

arXiv:2610.10560v1 Announce Type: cross Abstract: AI foundation models pretrained on weather and climate data are increasingly fine-tuned to Earth science tasks well beyond weather forecasting. Their

Strategic Investment Decision Making for Value Creation in Energy Transition: A Reinforcement Learning Approach

arXiv:2610.10768v1 Announce Type: cross Abstract: The global challenge of climate change has driven significant steps to reduce CO2 emissions, guided by international agreements like the Paris Agreeme

Strix halo + CMP 170HX setup

A bit of backstory : i got lucky in August and was able to grab a CMP 170 HX 8GB for around 500 on alibaba. I tried later to get a second one for around 1k but my order got cancelled and prices went t

SV-TAD: Native Sparse Convs for Efficient Temporal Action Detection

arXiv:2610.11579v1 Announce Type: new Abstract: To adapt billion-parameter Vision Transformers for long-video understanding, recent methods freeze the backbone and train lightweight convolutional modu

SWE-Journey: Towards More Realistic Evaluation of Coding Assistants through Long-Horizon, Multi-Turn Interaction

arXiv:2610.11559v1 Announce Type: cross Abstract: Coding assistants such as Claude Code and Codex have become a major application of LLM agents, yet existing benchmarks remain far from real-world use,

Symbolic Density Estimators for Unnormalized Distributions

arXiv:2610.10807v1 Announce Type: new Abstract: Estimating the symbolic or analytical form of probability density functions (PDFs) from observed samples is a fundamental challenge in statistical and c

Syn-Omni: Structured Specialization and Progressive Collaboration for Omnimodal Embeddings

arXiv:2610.12256v1 Announce Type: cross Abstract: Omnimodal embeddings naturally involve both shared representations and modality-specific features across heterogeneous inputs. However, existing omnim

Tell Robot What Not to Do: A Negation Understanding Perspective

model-releasesarxiv-cs-ro

arXiv:2610.11952v1 Announce Type: new Abstract: Instruction following enables robots to perform diverse tasks specified in natural language, making it a fundamental capability for human-robot interact

tencent/Youtu-Parsing-Omni · Hugging Face

Youtu-Parsing-Omni is a compact (5B) omni-modal parsing model. Given a single input — a document page, a natural image, a chart / flowchart, a geometry figure, an audio clip or an audio-visual video —

Test-Time Compute for Tabular Foundation Models: Mechanisms, Gains, and Limits

arXiv:2610.12005v1 Announce Type: new Abstract: Which forms of test-time compute improve the predictions of strong pretrained tabular foundation models (TFMs)? We systematically study this along three

Tested Mellum2.1-12B-A2.5B on PI Coding Agent - surprisingly usable, but not great at one-shot projects

I tested Mellum2.1-12B-A2.5B (Q8) locally using Pi and llama-server. All five tests were one-shot. Results were pretty mixed: - Pelican SVG, Browser OS, Minecraft: Poor results. - Bouncing Hexagon: Ph

TestJack: Should you trust the results in coding benchmarks? Agentic Coding Benchmarks Auditing via Evaluator Evolution

arXiv:2610.10619v1 Announce Type: cross Abstract: Large language model (LLM) agents are rapidly reshaping software engineering, accompanied by an explosion of new code benchmarks. Yet nearly all exist

The challenge for Google post-Gemini 4 will be what they do with a good model. Anthropic & OpenAI show we are moving towards a single interf…

model-releasesethan-mollick--x

The challenge for Google post-Gemini 4 will be what they do with a good model. Anthropic & OpenAI show we are moving towards a single interface for many tasks with orchestrator agents. The Gemini 3 er

ThinkingBox: Solving an agent task once vs. solving it 20/20: 507 stateful workflows graded on terminal database state [R]

model-releasesr-machinelearning

Figure 1b from our paper Disclosure: I'm one of the authors (Microsoft). The paper, code, dataset are public and ThinkingBox is on Hugging Face OpenEnv as well. Raw evaluation trajectories are not rel

TKCAM: Text and Keyframe to Camera Trajectory Generation

arXiv:2610.11105v1 Announce Type: new Abstract: Generating high-quality and controllable camera motion is essential for AI-assisted cinematography, video synthesis, and 3D scene understanding. We intr

TokenRouter: Efficient Serving System for Token-Level LLM Routing

arXiv:2610.12242v1 Announce Type: new Abstract: Large language model (LLM) routing distributes inference work across different models, advancing the cost-quality Pareto frontier of LLM serving. While

Towards Unified Evaluation of Prompt Enhancers for Video Generation

arXiv:2610.11736v1 Announce Type: new Abstract: Modern video generators can realize increasingly complex visual narratives, positioning the prompt enhancer (PE) as a critical bridge from concise user

TRACE: Diagnosing Verifier Brittleness in Agentic Evaluation

arXiv:2610.11678v1 Announce Type: new Abstract: Verifier scores now serve as both benchmark metrics and training rewards for large language model (LLM) agents, and a change in score is routinely read

Training on the Future: A Delay-Aware Audit of Test-Time Adaptation for Time-Series Forecasting

arXiv:2610.12232v1 Announce Type: new Abstract: Test-time adaptation (TTA) methods for time-series forecasting update a deployed model, or a small adapter around it, from incoming ground truth. But th

TRL v1.15 is out, and it’s an absolute banger of a release for memory-efficient post-training. The main change: SFT, DPO, KTO, GRPO, RLOO an…

model-releasesclem-delangue--x

TRL v1.15 is out, and it’s an absolute banger of a release for memory-efficient post-training. The main change: SFT, DPO, KTO, GRPO, RLOO and Distillation now use a fused LM head by default. Instead o

ttok 1.0

model-releasessimon-willison

Release: ttok 1.0 I released ttok 0.4, ran uv tool upgrade ttok, piped a file into the new version... and realized that it was defaulting to the GPT-4 tokenizer when it should very clearly default to

TypedBench: A Benchmark for Calibration, Framing Sensitivity, and Cost in System One Decision Models

arXiv:2610.11392v1 Announce Type: new Abstract: System One models output calibrated probabilities over typed answers such as categorical choices, ordinal levels, or binary outcomes, via a non-generati

UltraLight Luma: A Novel Edge-Deployable Perception Network for Crop-Row Segmentation in Agricultural Robotics

model-releasesarxiv-cs-ro

arXiv:2610.11764v1 Announce Type: new Abstract: Reliable crop-row perception is essential for autonomous agricultural robots, but low-cost deployment is constrained by computation, memory, power, and

Uncovering and Fixing Collider Bias in Bayesian PINNs

arXiv:2610.11737v1 Announce Type: cross Abstract: Bayesian physics-informed neural networks (B-PINNs) are a popular framework for parameter and state inference from sparse or noisy observations. They

Universal Textual Teaching for LLMs

arXiv:2610.12114v1 Announce Type: new Abstract: Knowledge distillation (KD) transfers knowledge from stronger Teacher models to weaker Student models, but most methods require training the Student par

Use and Disuse: Intent-Structured Experience Consolidation for Memory and Learning in LLM Agents

arXiv:2610.12124v1 Announce Type: new Abstract: The evolution of Large Language Model agents from single-task execution to long-term autonomous operation highlights the critical challenge of transform

Using LMs to Model the Effects of Context and Coreference during Sentence Comprehension

arXiv:2609.32119v2 Announce Type: replace Abstract: Language models (LMs) are often used as a tool to model human language processing. Recent studies suggest that severely restricting LMs' context win

V-ECE: Estimating General Expected Calibration Errors

arXiv:2602.24230v2 Announce Type: replace-cross Abstract: In probabilistic classification, calibration error (CE) measures the average divergence of predicted probabilities f(X) from P(Y|f(X)), the tr

VibeEdit: Image Editing with Canvas Instructions

arXiv:2610.12229v1 Announce Type: cross Abstract: In text-guided image editing, describing the desired change is often straightforward, but identifying the intended object or region can be cumbersome,