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arXiv:2610.16232v1 Announce Type: new Abstract: In-silico optimization of nucleic acids relies on predictive oracles that imperfectly capture biological function, so sequences optimized against one mo

agentsarxiv-cs-lg

Content type

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Autoregressive Decoding as a Martingale: Characterizing the Stochastic Dynamics of LLM Generation

DGX agent

arXiv:2610.16041v1 Announce Type: new Abstract: Large language models (LLMs) have achieved remarkable success across a wide range of language tasks. At their core, autoregressive LLMs are conditional

model-releasesarxiv-cs-lg

14 Oct 2026

Axiom-0: Hierarchical Self-Refinement for Vision-Language-Action Policies

arXiv:2610.14155v1 Announce Type: cross Abstract: Reliable manipulation requires policies that generalize across tasks, layouts, and object interactions. Vision-language-action (VLA) models combine pr

safetyarxiv-cs-cv

B-Human '26 - Scalable Team Play up to 11 vs. 11

arXiv:2610.14733v1 Announce Type: new Abstract: B-Human won multiple competitions in the Middle Division of the new Humanoid Soccer League in 2026. In addition to regular matches with three or five pl

researcharxiv-cs-ro

b11607

chat: replace output string with parts (#30389) chat: replace output string with parts reserve first Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/5563975

b11608

server : escape the special tokens without std::regex (#30243) The d1-omni and kev prompts escape '<|name|>' in the request text with std::regex_replace. libstdc++ recurses for each char of the name,

b11609

webgpu: (Fix CI) fix mul_mat_id with duplicate expert ids (#30451) Fix mm-id of webgpu in the case of ids duplication formatting fix comments to avoid breaking up sentences in comments Website: https:

b11612

unicode : add opt-in NFC normalization for Unigram tokenizers (#30390) unicode : add opt-in NFC normalization for Unigram tokenizers Note: used help from Codex, Sol 6.1 Medium Fixing initial bot comme

b11617

vulkan: fix compile error (#30495) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/55839699 macOS/iOS: macOS Apple Silicon (arm64) macOS Apple Silicon (arm6

b11619

models: drop the t_embd expand of the embedding graphs (#30461) These graphs only produce embeddings, and build_pooling() already expands its output for every pooling type, so the expand at the end of

b11620

opencl: fix q8_0 dp4a mul_mat_id and mark PREC_F32 mul_mat_id unsupported for adreno (#30365) opencl: fix min handling for moe q8_0 dp4a GEMM Co-authored-by: Hongqiang Wang wangh@qti.qualcomm.com open

b11621

opencl: use buf+offset instead of subbuffer for adreno moe expert sort (#30418) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/55971785 macOS/iOS: macOS Ap

b11622

jinja : write floats in tojson as Python does (#30362) tojson printed floats through a C++ stream (6 significant digits, no '.0'), so 48.858844 became 48.8588 and 1.0 became 1 in tool definitions, too

b11623

cuda : use SIMT implicit GEMM conv2d on AMD without WMMA (#30325) cuda : use SIMT implicit GEMM conv2d on AMD without WMMA Assisted-by: Claude Opus cuda : update conv2d SIMT comment cuda : skip SIMT c

b11624

ggml : improve RPC tensor transfer logs (#30481) add rpc_log_format_size() and print byte counts in KiB/MiB/GiB across the RPC client, server and transport traces add rpc_log_format_tensor() and inclu

b11632: cuda, hip: GDN chunked kernel (#29353)

cuda, hip: GDN chunked kernel Ported-from: tetherto#257 Source-commit: 53f0027 Co-authored-by: Aman Gupta aman.gupta@tether.io fix older builds review fixes cuda: enable GDN MMA on tested Ampere and A

Background2Background: a self-supervised background removal framework for high dimensional microscopy

arXiv:2610.17615v1 Announce Type: cross Abstract: High-dimensional microscopy captures features across space, time, and spectrum, but complex backgrounds obscure signals. We present Background2Backgro

Backward Conformal Prediction under Covariate Shift

arXiv:2610.16048v1 Announce Type: new Abstract: Backward conformal prediction (BCP) fixes the size of a prediction set and estimates its miscoverage, but assumes calibration and test data are exchange

BandPC: Learning Residual-Band Preconditioner Combinations for Flexible Conjugate Gradient Solvers

arXiv:2609.37140v1 Announce Type: cross Abstract: The conjugate gradient (CG) method is a classical iterative solver for sparse symmetric positive definite (SPD) linear systems, but its convergence st

Agents

Banger paper from Stanford, Together AI, and colleagues. Why is this an interesting paper? Today's LLM agents must write out every reasoning…

Banger paper from Stanford, Together AI, and colleagues. Why is this an interesting paper? Today's LLM agents must write out every reasoning step as text before they can search, run code, or take acti

agentsdair-ai--x

Barrier-Constrained Guidance For Real-time Asynchronous VLA Execution

arXiv:2610.14997v1 Announce Type: new Abstract: While asynchronous execution enables VLA models to operate in real-time environments by predicting the next chunk during execution, it inevitably introd

safetyarxiv-cs-ro

BARTER: Compact Dynamic Sparse Training with Standard Dense Kernels

arXiv:2610.16147v1 Announce Type: new Abstract: Dynamic sparse training (DST) aims to reduce training costs while maintaining accuracy. Existing DST methods mask out parameters but keep matrix dimensi

Barycentric Anchored Weight Search for Robust Model Merging

arXiv:2610.14017v1 Announce Type: cross Abstract: We propose Barycentric Anchored Search, a post-hoc weight-space procedure for improving fine-tuned vision models under distribution shift without addi

Barycentric Guidance: Turning Foundation Image Editors into Continuous Affective Controllers

arXiv:2610.16892v1 Announce Type: new Abstract: Emotions are expressed on a continuum and are naturally described in the valence-arousal (VA) space. Existing VA-based image editors are typically train

BaT-SAM: Introducing Inductive Bias into SAM via a Mixture of Convolutional Experts for Brain Tumor Segmentation

model-releasesarxiv-cs-cv

arXiv:2610.15330v1 Announce Type: new Abstract: Accurate brain tumor segmentation from magnetic resonance imaging (MRI) is essential for diagnosis and treatment planning; however, manual delineation i

BAT3R: Robust Online 3D Reconstruction with Bayesian Adaptive State Updates

arXiv:2610.16330v1 Announce Type: new Abstract: Feed-forward transformer models have driven remarkable progress in 3D vision,yet their quadratic complexity renders them impractical for long video sequ

Bayesian Nonparametric Thompson Sampling for Multi-Armed Bandits

arXiv:1808.02932v5 Announce Type: replace-cross Abstract: In stochastic multi-armed bandits, rewards are generated by an unknown distribution; the world's reward uncertainty induces the exploration-ex

researcharxiv-cs-lg

Applications

Bayesian Optimization of CVaR with Unknown Hyperparameters

arXiv:2610.18306v1 Announce Type: new Abstract: We study Bayesian optimization of the Conditional Value-at-Risk (CVaR) of an expensive black-box function that depends on a decision and an environmenta

applicationsarxiv-cs-lg

Bayesian Optimization under Uncertainty for Training a Scale Parameter in Stochastic Models

arXiv:2510.06439v2 Announce Type: replace Abstract: Hyperparameter tuning is a challenging problem especially when the system itself involves uncertainty. Due to noisy function evaluations, optimizati

Bayesian Test-Time Inference of Task-Aligned Similarity from Weak Interactive Feedback

arXiv:2610.18656v1 Announce Type: new Abstract: Language model systems repeatedly make test-time decisions by comparing similarity: they retrieve exemplars, rank candidates, and revise responses. Yet

researcharxiv-cs-lg

Before Attention Sinks Form: Hidden-State Geometry Reveals and Modulates Their Formation

arXiv:2610.16745v1 Announce Type: new Abstract: Attention sinks are usually studied after they have formed. We ask whether a measurable hidden-state change appears beforehand and whether changing that

researcharxiv-cs-lg

Before We Act: Learning Action-Conditioned Team-Response Beliefs for Decentralized Multi-Robot Manipulation

arXiv:2610.14551v1 Announce Type: new Abstract: In multi-robot manipulation, an action's value depends on how teammates respond. We present method{} (Cooperative Action--Response Belief Estimation), a

safetyarxiv-cs-ro

// Behavioral Self-Rewarding for SWE agents // It's standard practice to train SWE agents on binary test rewards. This paper shows the probl…

// Behavioral Self-Rewarding for SWE agents // It's standard practice to train SWE agents on binary test rewards. This paper shows the problem with that. When every trajectory in a group passes, or ev

safetydair-ai--x

Tutorials

BehaviorFormer: Discovering Behavioral Patterns via Clusterable Next-Token Prediction

arXiv:2610.16322v1 Announce Type: new Abstract: Discovering behavioral patterns in open-ended games is challenging due to the lack of clear objectives or ground-truth annotations. In this work, we ext

tutorialsarxiv-cs-lg

Agents

Behavioural self-monitoring for autonomous earth observation agents: The attribute reliability monitor (ARM)

arXiv:2610.18548v1 Announce Type: new Abstract: Language and vision language models can support autonomous systems, but changing operating conditions may compromise the reliability of their semantic o

agentsarxiv-cs-ro

Belief Embedding Tree Search

arXiv:2610.15046v1 Announce Type: cross Abstract: Beliefs in a Partially Observable Markov Decision Process (POMDP) are posterior distributions over the hidden state given the agent's history of actio

safetyarxiv-cs-lg

Belief Space Planning for Risk Signal Temporal Logic via Mixed-Integer Convex Programming

arXiv:2610.16696v1 Announce Type: new Abstract: Signal Temporal Logic (STL) specifies robot tasks with spatio-temporal requirements, and its robustness semantics allow planning by trajectory optimizat

researcharxiv-cs-ro

Hardware

BELT : BEhavior-Aligned Low-Rank KV Cache Compression with Learned Top-k Rank Allocation

arXiv:2610.17966v1 Announce Type: new Abstract: Long-context inference makes the key-value (KV) cache a major memory bottleneck for large language models. We propose BELT, a low-rank KV cache compress

hardwarearxiv-cs-lg

Benchmarking Deep Learning Models for Anomaly Detection in Real-World Cloud Telemetry

arXiv:2610.15818v1 Announce Type: new Abstract: Modern cloud platforms generate high-dimensional, noisy telemetry from thousands of microservices. Unlike classical anomaly detection benchmarks, cloud

Benchmarking Interaction-Oriented Aerial Mobility across Heterogeneous Environments

model-releasesarxiv-cs-ro

arXiv:2610.18381v1 Announce Type: new Abstract: Aerial mobile manipulation requires unmanned aerial vehicles (UAVs) to traverse heterogeneous environments such as indoor and outdoor domains, and conne

Benchmarking Multimodal Large Language Models for Zero-Shot Human-Object Interaction

model-releasesarxiv-cs-cv

arXiv:2610.18161v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have demonstrated strong zero-shot reasoning across diverse domains, but their potential for Human-Object Inter

Benchmarking Self-Supervised 3D Medical Vision Foundation Models and Transferability Estimation

model-releasesarxiv-cs-cv

arXiv:2610.17573v1 Announce Type: new Abstract: Self-supervised pretraining has expanded the pool of 3D medical foundation models, but published evaluations use different datasets, endpoints and fine-

Benchmarks are becoming the core competency of any company. Our company mission is to build the world’s best models for document processing.…

model-releasesjerry-liu--x

Benchmarks are becoming the core competency of any company. Our company mission is to build the world’s best models for document processing. This also means that we have to build the world’s best benc

Benchmarks Are Not Atomic: Composition-Aware LLM Evaluation using BenchHub

arXiv:2506.00482v2 Announce Type: replace Abstract: LLM benchmarks are often treated as coherent measurement units, yet they are heterogeneous collections of instances spanning diverse domains, skills

Tutorials

Better Capturing Interactions Between Products in~Retail: Revisited Negative Sampling for~Basket Choice Modeling

arXiv:2610.17963v1 Announce Type: new Abstract: Brick-and-mortar retailers face many different challenges that involve understanding thoroughly its products catalog and customer preferences. In partic

tutorialsarxiv-cs-lg

Tutorials

Better together? A performance theory of human-machine skill policies under generalization difficulty

arXiv:2610.16863v1 Announce Type: cross Abstract: Organizations pairing a human and a machine on a task decide, often by default, which executes each instance and what happens when both do. We account

tutorialsarxiv-cs-lg

Beyond a Better Score: Long-Horizon Agentic ML Development and Evaluation Protocol for Physics Time Series

arXiv:2610.14024v1 Announce Type: new Abstract: Physics time-series data are central to fundamental discoveries involving dark matter, neutrinos, and gravitational waves. Machine learning has shown st

Beyond Adjacent Layers: Graph-Guided Layer Fusion for Compressing Large Language Models

arXiv:2610.15159v1 Announce Type: new Abstract: Existing depth-compression methods for large language models (LLMs) score layers individually or group only adjacent or contiguous layers, implicitly as