v0.20.3
What's Changed Gemma 4 Tool Calling improvements Added latest models to Ollama App OpenClaw fixes for launching TUI Full Changelog : v0.20.2...v0.20.3
ollama
/
ollama
Public
-
Notifications You must be signed in to change notification settings
-
Fork 15.4k
-
Star 168k
v0.20.3
Latest
Latest
Compare
Choose a tag to compare
Sorry, something went wrong.
Filter
Loading
Sorry, something went wrong.
Uh oh!
There was an error while loading. Please reload this page.
No results found
View all tags
github-actions
released this
07 Apr 05:19
v0.20.3
8c8f8f3
This commit was created on GitHub.com and signed with GitHub’s verified signature.
GPG key ID: B5690EEEBB952194
Verified
Learn about vigilant mode.
What's Changed
-
Gemma 4 Tool Calling improvements
-
Added latest models to Ollama App
-
OpenClaw fixes for launching TUI
Full Changelog: v0.20.2...v0.20.3
Assets 18
Loading
Uh oh!
There was an error while loading. Please reload this page.
👍 1 donatas-xyz reacted with thumbs up emoji 🎉 5 ameaninglessname, yougrandpa, anothernoise, mvvvv, and Monkeygamer2010 reacted with hooray emoji ❤️ 2 hl2guide and Monkeygamer2010 reacted with heart emoji 🚀 2 hl2guide and Monkeygamer2010 reacted with rocket emoji
All reactions
-
👍 1 reaction
-
🎉 5 reactions
-
❤️ 2 reactions
-
🚀 2 reactions
7 people reacted
Sign in to highlight and annotate this article
Conversation starters
Daily AI Digest
Get the top 5 AI stories delivered to your inbox every morning.
More about
llamamodellaunch
Sampling Sphere Packings with Continuum Glauber Dynamics
arXiv:2601.18748v2 Announce Type: replace Abstract: Continuum Glauber dynamics is a spatial birth-death process whose stationary distribution is a Gibbs distribution. We establish a spectral gap for Continuum Glauber dynamics applied to Gibbs point processes with repulsive pair potentials, a well-known special case of which is the hard sphere model. For arbitrary-range repulsive pair potentials, we show that a continuous version of Spectral Independence suffices to establish a spectral gap. This extends the regime of activity for which Continuum Glauber dynamics is known to mix, yielding a simple efficient sampling algorithm for arbitrary-range pair potentials that matches the known efficient sampling regime for finite-range pair potentials currently based on specialized algorithms. As a c
Faster All-Pairs Minimum Cut: Bypassing Exact Max-Flow
arXiv:2511.10036v2 Announce Type: replace Abstract: All-Pairs Minimum Cut (APMC) is a fundamental graph problem that asks to find a minimum $s,t$-cut for every pair of vertices $s,t$. A recent line of work on fast algorithms for APMC has culminated with a reduction of APMC to $\mathrm{polylog}(n)$-many max-flow computations. But unfortunately, no fast algorithms are currently known for exact max-flow in several standard models of computation, such as the cut-query model and the fully-dynamic model. Our main technical contribution is a sparsifier that preserves all minimum $s,t$-cuts in an unweighted graph, and can be constructed using only approximate max-flow computations. We then use this sparsifier to devise new algorithms for APMC in unweighted graphs in several computational models: (
Unbiased Insights: Optimal Streaming Algorithms for $\ell_p$ Sampling, the Forget Model, and Beyond
arXiv:2508.07067v3 Announce Type: replace Abstract: We study $\ell_p$ sampling and frequency moment estimation in a single-pass insertion-only data stream. For $p \in (0,2)$, we present a nearly space-optimal approximate $\ell_p$ sampler that uses $\widetilde{O}(\log n \log(1/\delta))$ bits of space and for $p = 2$, we present a sampler with space complexity $\widetilde{O}(\log^2 n \log(1/\delta))$. This space complexity is optimal for $p \in (0, 2)$ and improves upon prior work by a $\log n$ factor. We further extend our construction to a continuous $\ell_p$ sampler, which outputs a valid sample index at every point during the stream. Leveraging these samplers, we design nearly unbiased estimators for $F_p$ in data streams that include forget operations, which reset individual element fre
Knowledge Map
Connected Articles — Knowledge Graph
This article is connected to other articles through shared AI topics and tags.
More in Models
Systematic Approach to Hyperbolic Quantum Error Correction Codes
arXiv:2504.07800v2 Announce Type: replace-cross Abstract: Quantum error correction codes defined on hyperbolic lattices leverage the unique geometric properties of the hyperbolic space to enhance the performance of quantum error correction. By embedding qubits in hyperbolic lattices, these codes achieve higher encoding rates and lower qubit overhead compared to those defined on conventional Euclidean lattices. Building on recent advances in hyperbolic crystallography, we introduce a unified framework for the systematic construction and scalable benchmarking of CSS quantum error correction codes on hyperbolic lattices. A central component of this framework is the Hyperbolic Cycle Basis algorithm, which employs graph-theoretic methods to efficiently identify all plaquette cycles (parity-chec
LiquiLM: Bridging the Semantic Gap in Liquidity Flaw Audit via DCN and LLMs
arXiv:2604.03860v1 Announce Type: new Abstract: Traditional consensus mechanisms, such as Proof of Stake (PoS), increasingly reveal an excessive dependency on large liquidity providers. Although the Proof of Liquidity (PoL) mechanism serves as a critical paradigm for incentivizing sustained liquidity provision and ensuring market stability, its transition from asset staking to active liquidity management significantly increases the complexity of underlying smart contract economic models and interaction logic. This renders hidden liquidity logic flaws difficult to detect via traditional methods, seriously threatening the system stability and user asset security of mainstream DeFi and emerging PoL ecosystems. To address this, we propose the LiquiLM framework, which integrates Large Language
Explainability-Guided Adversarial Attacks on Transformer-Based Malware Detectors Using Control Flow Graphs
arXiv:2604.03843v1 Announce Type: new Abstract: Transformer-based malware detection systems operating on graph modalities such as control flow graphs (CFGs) achieve strong performance by modeling structural relationships in program behavior. However, their robustness to adversarial evasion attacks remains underexplored. This paper examines the vulnerability of a RoBERTa-based malware detector that linearizes CFGs into sequences of function calls, a design choice that enables transformer modeling but may introduce token-level sensitivities and ordering artifacts exploitable by adversaries. By evaluating evasion strategies within this graph-to-sequence framework, we provide insight into the practical robustness of transformer-based malware detectors beyond aggregate detection accuracy. This
Systematic Integration of Digital Twins and Constrained LLMs for Interpretable Cyber-Physical Anomaly Detection
arXiv:2604.03790v1 Announce Type: new Abstract: Cyber attacks targeting Industrial Control Systems (ICS) have become increasingly sophisticated and hard to identify. Detecting such attacks requires integrating low-level behavioral cues with high-level semantic interpretation, a capability that traditional anomaly detectors lack. This paper presents a Digital Twin (DT)-driven hybrid detection approach that combines deterministic heuristics with systematic, constrained Large Language Model (LLM) reasoning to achieve real-time incident detection. The DT maintains a synchronized, feature-enriched representation of the Secure Water Treatment (SWaT) process, deriving behavioral descriptors. Heuristics identify characteristic signatures of spoofing, valve forcing, denial-of-service, and bias drif
Discussion
Sign in to join the discussion
No comments yet — be the first to share your thoughts!