EventVLA: Event-Driven Visual Evidence Memory for Long-Horizon Vision-Language-Action Policies
Paper • 2606.20092 • Published
AI & ML interests
Computer Vision
Recent Activity
View all activity
Papers
Imagine Before You Predict: Interleaved Latent Visual Reasoning for Video Event Prediction
RIVER: A Real-Time Interaction Benchmark for Video LLMs
ganlinyang
submitted a
paper to Daily Papers about 1 hour ago
Post
192
Shipped v0.1.2 of vtx — a minimalist coding agent for the terminal.
Most agentic CLIs ship 10k+ token system prompts. Vtx is ~2,200. Less prompt overhead means more room for your code in the model's context window.
Vtx is a from-scratch Python implementation of the design philosophy behind pi-mono — same principles, pure Python, no transpiled runtime.
What ships out of the box:
→ Textual TUI + headless CLI (vtx -p "fix the failing test")
→ 49 LLM provider gateways, all declared in a single provider.yaml
→ 5 core tools (read / edit / write / bash / find) plus web search and fetch
→ Session tree with compaction, handoff, and resume
→ AGENTS.md / CLAUDE.md auto-discovery
→ Skills system — drop SKILL.md files in .agents/skills/ and they become slash commands
→ Two OAuth flows (GitHub Copilot device flow, OpenAI Codex PKCE)
→ Two-mode permissions: prompt (default) or auto, with a safe-command allowlist
This release adds a proper extension system. Register new LLM-callable tools, intercept tool calls, hook lifecycle events, and add slash commands from a single register(api) function in a Python file under ~/.vtx/agent/extensions/. Extensions can override built-in tools by name and chain handler logic across subscribers.
Apache 2.0. uv tool install vtx-coding-agent and you're running.
GitHub: https://github.com/OEvortex/vtx-coding-agent
PyPI: https://pypi.org/project/vtx-coding-agent
Built in the open. Feedback, extensions, and PRs welcome.
Most agentic CLIs ship 10k+ token system prompts. Vtx is ~2,200. Less prompt overhead means more room for your code in the model's context window.
Vtx is a from-scratch Python implementation of the design philosophy behind pi-mono — same principles, pure Python, no transpiled runtime.
What ships out of the box:
→ Textual TUI + headless CLI (vtx -p "fix the failing test")
→ 49 LLM provider gateways, all declared in a single provider.yaml
→ 5 core tools (read / edit / write / bash / find) plus web search and fetch
→ Session tree with compaction, handoff, and resume
→ AGENTS.md / CLAUDE.md auto-discovery
→ Skills system — drop SKILL.md files in .agents/skills/ and they become slash commands
→ Two OAuth flows (GitHub Copilot device flow, OpenAI Codex PKCE)
→ Two-mode permissions: prompt (default) or auto, with a safe-command allowlist
This release adds a proper extension system. Register new LLM-callable tools, intercept tool calls, hook lifecycle events, and add slash commands from a single register(api) function in a Python file under ~/.vtx/agent/extensions/. Extensions can override built-in tools by name and chain handler logic across subscribers.
Apache 2.0. uv tool install vtx-coding-agent and you're running.
GitHub: https://github.com/OEvortex/vtx-coding-agent
PyPI: https://pypi.org/project/vtx-coding-agent
Built in the open. Feedback, extensions, and PRs welcome.
qishisuren
submitted a
paper to Daily Papers 9 days ago
yanziang
authored a
paper 13 days ago
linghan199
authored a
paper 13 days ago
Fix remaining Transformers v5 crash: guard llm_config and to_dict() for None (follow-up to `e980c02`)
#13 opened 17 days ago
by 
KBayoud
Fix KeyError in __init__ when vision_config is empty (Transformers v5 compatibility)
#12 opened 17 days ago
by KBayoud
Eurayka
submitted a
paper to Daily Papers 19 days ago
heroding77
submitted a
paper to Daily Papers 26 days ago
Kaining
authored a
paper 28 days ago
Kaining
submitted a
paper to Daily Papers 29 days ago
yuezhengrong
authored a
paper about 1 month ago
yuezhengrong
submitted a
paper to Daily Papers about 1 month ago
yuezhengrong
authored 7
papers about 1 month ago
MUSES: 3D-Controllable Image Generation via Multi-Modal Agent Collaboration
Paper • 2408.10605 • Published • 2
TimeSuite: Improving MLLMs for Long Video Understanding via Grounded Tuning
Paper • 2410.19702 • Published • 1
VideoChat-A1: Thinking with Long Videos by Chain-of-Shot Reasoning
Paper • 2506.06097 • Published • 1
LVAgent: Long Video Understanding by Multi-Round Dynamical Collaboration of MLLM Agents
Paper • 2503.10200 • Published
VideoChat-R1.5: Visual Test-Time Scaling to Reinforce Multimodal Reasoning by Iterative Perception
Paper • 2509.21100 • Published • 1
UniFlow: A Unified Pixel Flow Tokenizer for Visual Understanding and Generation
Paper • 2510.10575 • Published • 2
Beyond Textual CoT: Interleaved Text-Image Chains with Deep Confidence Reasoning for Image Editing
Paper • 2510.08157 • Published