model releases

Agentic-TTT: Training test-time policy for test-time training

arXiv:2610.12002v1 Announce Type: cross Abstract: Test-time training (TTT) adapts an LLM's parameters using signals derived from test inputs, and can make striking improvements in pre-specified settin

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AgentTime: Can Agents Estimate and Control Their Own Runtime?

DGX agent

arXiv:2610.09944v2 Announce Type: replace Abstract: An essential control of AI agents is their ability to manage runtime. This ability requires a sense of time-awareness, to predict and estimate wall-

model-releasesarxiv-cs-ai

9 Oct 2026

Amortized Off-Policy Evaluation for LLMs

arXiv:2610.10848v1 Announce Type: new Abstract: Accurate evaluation is central to selecting which LLM to deploy, yet testing a candidate on live traffic exposes real users to an unvetted model. Teams

An Explainable Header-Centric Framework for Large-Scale Semantic Table Interpretation and Data Quality Assessment

arXiv:2610.10541v1 Announce Type: new Abstract: Knowledge Graph (KG) quality depends not only on downstream graph validation, but also on the quality of tabular metadata used before integration. In me

Anthropic’s AI gave Philadelphia police a fake tip about an unsolved homicide

model-releasesthe-verge-ai

An Anthropic AI model provided false information about an unsolved homicide to a Philadelphia Police Department (PPD) tipline, according to a report from 6abc. In a statement released on Friday, the P

Arbiter: Detecting Interference in LLM Agent System Prompts

arXiv:2603.08993v2 Announce Type: replace-cross Abstract: System prompts for LLM-based coding agents are software artifacts that govern agent behavior, yet lack the testing infrastructure applied to c

ASPIRE: Saddle-Point Discovery through Set Prediction and Physical Refinement

arXiv:2610.10969v1 Announce Type: new Abstract: Predicting thermally activated diffusion and defect evolution with event-driven models requires identifying atomic rearrangement mechanisms and their ac

b11516

hexagon: fix IM2COL patch-embed DMA ring overflow (#30189) hexagon: fix IM2COL patch-embed DMA ring overflow The exact-tiling (stride == kernel, no pad/dilation) IM2COL DMA kernel issues ICKH DDR->VTC

b11517

CUDA: pass src1 precision to host MMQ config helpers (#30168) CUDA: pass src1 precision to host MMQ config helpers Signed-off-by: ynankani ynankani@nvidia.com make src1 prec explicit Signed-off-by: yn

b11518

metal: add the 128/96 flash attention kernels, accept every compiled pair (#30209) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/54260937 macOS/iOS: macOS

b11521

server: use port 9931 by default (#30159) server: use port 9931 by default revert unrelated changes Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/54269123

b11523

ci: fix Models Backend webgpu by supporting GGML_OP_DUP (#30216) The mixed batch path of PR-29622 writes the token rows with set_rows into a dup of the embeddings. WebGPU did not support DUP, so the d

b11524

musa: drop mp_21 from the default architectures (#30203) musa: drop mp_21 from the default architectures Signed-off-by: Xiaodong Ye xiaodong.ye@mthreads.com Address review comments Signed-off-by: Xiao

b11526

vulkan: fix rms_norm workgroup count overflow (#30145) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/54337638 macOS/iOS: macOS Apple Silicon (arm64) macOS

b11527

webgpu: use 2D workgroup dispatch for all the ops which use 1D dispatch (e.g., rms_norm) (#30219) remove 1D workgroups dispatching formatting Website: https://llama.app Attestations: https://github.co

b11528

meta : handle host views (#30217) meta : handle views of tensors allocated on the host A view shares the memory of its view_src, so ggml-alloc never allocates a view in the buffer of the split it land

b11529

ggml: fix OOB write in ggml_acc with negative offset (#30135) ggml_acc_impl narrowed a size_t offset to int32_t without checking that it fits, so a large offset could truncate to a negative int32_t. T

b11530

llama: keep the backend sampling graph static across ubatches (#30223) The reserve builds n_outputs_max_per_seq sampling chains per sampler, while a decode built one per output row, so the graph chang

b11531

chat : refactor API (#30210) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/54392536 macOS/iOS: macOS Apple Silicon (arm64) macOS Apple Silicon (arm64, Kle

b11532

model : use exact GELU for ModernBERT encoders (#30108) model : use exact GELU for ModernBERT encoders Assisted-by: Codex model : keep tanh GELU aliases on ggml_geglu Assisted-by: Claude Opus 5.5 mode

b11533

opencl: fix kernel compilation for a6x GPUs (#30176) opencl: skip kernel_cpy_f32_f32_pack on A6X to avoid shader compiler crash The A6x compiler backend found in iot device with a623 (E031.50.31.01) c

b11534

CUDA: Remove redundant CUDA copies after SSM_SCAN (#29807) CUDA: fuse copy of updated state snapshots into recurrent cache with ssm_scan CUDA: remove redundant cuda copies with K==1 (non spec-dec) sce

b11535

llama-bench: respect -fitc if bigger than required benchmark size (#28331) Assisted-By: opencode,llama.cpp,Qwen3.6-35B-A3B,Qwen3.8-27B Website: https://llama.app Attestations: https://github.com/ggml-

b11537

graph : reorder get_rows for embeddings (#30160) graph : reorder get_rows for embeddings cont : fix gemma4 and improve input embedding construction logic cont : add TODO for lora cont : fix raw embedd

b11538

CUDA: fix round issue, under MSVC the CPU and GPU agree (#30229) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/54453988 macOS/iOS: macOS Apple Silicon (ar

b11539

vendor: apply deep nested json patch from upstream (#30253) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/54488539 macOS/iOS: macOS Apple Silicon (arm64)

Banger paper from Meta Superintelligence Labs on self-improving agents. (bookmark it) It's hard to know exactly what drives self-improvement…

Banger paper from Meta Superintelligence Labs on self-improving agents. (bookmark it) It's hard to know exactly what drives self-improvement, since so many variables are at play (notes, skills, tool c

Banger paper from Meta Superintelligence Labs on user simulators for agent training. Agent RL setups usually let an assistant LLM play the u…

Banger paper from Meta Superintelligence Labs on user simulators for agent training. Agent RL setups usually let an assistant LLM play the user, so the simulated user is too cooperative and too explic

BEANS-Next and ROOTS: Broadening Audio-Language Capabilities for Bioacoustics

arXiv:2610.10663v1 Announce Type: cross Abstract: Bioacoustics and ethology encompass a wide range of audio understanding tasks, many of which stand to benefit from recent advances in large audio-lang

BEAT: Balanced Frequency Adaptive Tuning for Long-Term Time-Series Forecasting

arXiv:2501.19065v3 Announce Type: replace-cross Abstract: Long-term time-series forecasting supports a wide range of applications, including weather prediction and electricity demand planning. Frequen

before I joined Anthropic, I spent about 2 weeks hacking on this as a side project with Opus 4. It used the Agent SDK so it needed a constan…

before I joined Anthropic, I spent about 2 weeks hacking on this as a side project with Opus 4. It used the Agent SDK so it needed a constantly running process & didnt work that well but one prompt to

model-releasesthariq--x

BeliefScope: Diagnosing Evidence-Driven Revision and Pressure-Induced Shifts in Large Language Models

arXiv:2610.11305v1 Announce Type: new Abstract: A language model may revise the same proposition after receiving genuinely relevant evidence or after receiving directional user pressure that adds no r

Benchmark Designers Should 'Train on the Test Set' to Expose Exploitable Non-Visual Shortcuts

model-releasesarxiv-cs-cv

arXiv:2511.04655v2 Announce Type: replace Abstract: Multimodal LLMs can answer many questions in vision-centric benchmarks without looking at the image, using linguistic priors and skewed answer distr

Beyond Distributional Fidelity: Causal-Penalized Diffusion for Synthetic Tabular Data

arXiv:2610.11407v1 Announce Type: cross Abstract: Synthetic tabular generators are commonly optimized for distributional fidelity, but statistical similarity alone does not guarantee preservation of c

Beyond Imitation: A Framework and Benchmark for LLM-Assisted Peer Review

arXiv:2610.11087v1 Announce Type: new Abstract: The rapid growth of scientific publishing has strained peer review, particularly in machine learning, raising concerns about declining review quality an

Beyond Report Imitation: Clinically Aware Multi-Image Ultrasound Report Generation from Visible Evidence

arXiv:2610.11610v1 Announce Type: cross Abstract: Generating ultrasound reports from multiple images requires aggregating clinical evidence across views, yet archived key frames capture only part of t

Beyond Resolution: Object-to-Image Ratio Mismatch in Instance Retrieval

model-releasesarxiv-cs-cv

arXiv:2610.11489v1 Announce Type: new Abstract: Visual instance retrieval often fails when the same object appears at different apparent sizes in the query and gallery. We show that the dominant cause

BigMoeOnEdge+ – an Android chat app fork of BigMoeOnEdge (llama.cpp / GGUF)

I made BigMoeOnEdge+ (BigMoeOnEdge-plus), a fork of Helldez's BigMoeOnEdge, the engine that streams MoE experts from flash so models bigger than RAM can run on-device. It adds a full Android chat app

model-releasesr-ollama

BioBigBird: A Sparse Attention Model for Long-Range Dependency Processing in Biomedical Text

arXiv:2610.11430v1 Announce Type: new Abstract: While domain-specific Large Language Models (LLMs) have encoded vast biomedical knowledge, their limited context windows often hinder a deep understandi

Black-Box Forensics for Conversational LLM Agents

arXiv:2606.22698v2 Announce Type: replace-cross Abstract: As LLM-powered scams proliferate, black-box forensics for conversational LLM agents offers a path to accountability for systems hidden behind

Breaking the Group Size Barrier: Parameter-Efficient Group Dance Generation with Chain-of-Dancers

model-releasesarxiv-cs-cv

arXiv:2610.11237v1 Announce Type: new Abstract: Group dance generation aims to synthesize coordinated multi-dancer choreography from music, with broad applications in animation and interactive content

BrickBench: Evaluating Agentic Brick Design

arXiv:2610.12452v1 Announce Type: new Abstract: We propose BrickBench, a benchmark for agentic text-conditioned LEGO-set design. Given a prompt, an agent is tasked with producing an assembly that not

Build your own harness, folks. Reading papers like this makes me realize how underexplored harness engineering really is. The authors find t…

Build your own harness, folks. Reading papers like this makes me realize how underexplored harness engineering really is. The authors find that on whole-repository migration, GPT-5.6 Sol goes from 6.5

Bullish on this trend of making post-training more accessible. A new post-training era is upon us. If you work on agentic RL, long-context t…

Bullish on this trend of making post-training more accessible. A new post-training era is upon us. If you work on agentic RL, long-context tasks (a big focus today) are expensive, inefficient, and don

C-LoRA: Continual Low-Rank Adaptation for Pre-trained Visual Models

arXiv:2502.17920v2 Announce Type: replace Abstract: Pre-trained visual models have become fundamental in computer vision, but they face challenges in continual learning scenarios where data and tasks

Caloroga Media launches Linnet, an AI-assisted podcast studio that runs in the browser

model-releasessiliconangle

Podcast producer Caloroga Media has launched Linnet, a production studio that runs in a web browser with an artificial intelligence assistant built in. The company developed it from the workflow behin

Can AI Agents Learn Their Way to the Top? Evaluating Heuristic Learning in a Long-Running Game Agent Competition

arXiv:2610.12341v1 Announce Type: new Abstract: Adversarial games have driven advances from heuristic search to reinforcement learning, yet learning and adapting strategies from limited samples remain

Can Decision Models Understand Stance? Evaluating Jev Against General-Purpose LLMs

arXiv:2610.11901v1 Announce Type: new Abstract: Stance detection requires identifying an author's attitude toward a given target, sometimes based on conversational context. Jev, a specialized decision