Papersby GlyphSteerDuplex: Steerable Duplex Speech Dialogue Models research paper by Scale AI, 2026
Scale AI · Multimodal and robotics · Sep 11, 2026 · 3 citations · 6 upvotes
What it shows
A full-duplex speech model that follows spoken instructions on tone, persona, pace and voice, with a benchmark of 390 prompts to test it.
By Utkarsh Tyagi, Ramaneswaran Selvakumar, Advait Gosai and 13 more · arXiv 2609.12623 · PDF
Summarised by hand from the abstract.
More from Scale AI
All 25Root-Cause Attribution Is a Search Problem: Continual Search for Long-Horizon Agent FailuresContinual Search improves automated root-cause attribution in long agent execution traces by iteratively prompting diagnosis until unresolved evidence is found.
Scale AI5 upvotesRead →Studying Without a Syllabus: Task-Agnostic Environment PreprocessingAn agent can explore unfamiliar environments without task-specific guidance to build reusable artifacts that reduce later inference costs, though larger study budgets do not always improve results.Scale AI1 citations4 upvotesRead →HarnessOpt-Bench: Evaluating LLMs at Harness OptimizationHarnessOpt-Bench measures how well frontier LLMs iteratively improve agent harnesses under constrained evaluation budgets, revealing substantial variation across models and tasks.Scale AI12 citations35 upvotesRead →Model or Harness? An Interaction-Centric Taxonomy for Localizing Agent FailuresAn interaction-centric taxonomy localizes agent failures to specific component interactions to guide targeted repairs across diverse architectures.Scale AI11 citations10 upvotesRead →SWE-INTERACT: Reimagining SWE Benchmarks as User-Driven Long-Horizon Coding SessionsSWE-Interact presents a testbed that evaluates coding agents in realistic multi-turn, user-driven software engineering scenarios, revealing significant gaps between single-turn performance and interactive task completion.Scale AI23 citations7 upvotesRead →Not Every Rubric Teaches Equally: Policy-Aware Rubric Rewards for RLVRPOW3R is a policy-aware framework for reinforcement learning with rubric-based rewards that adapts criterion weights during training to improve policy optimization while preserving human-defined criteria importance.Scale AI13 citations5 upvotesRead →Reward Hacking in Rubric-Based Reinforcement LearningResearch examines reward hacking in rubric-based reinforcement learning, identifying verifier failure and rubric-design limitations as key sources of divergence between training and evaluation metrics.Scale AI33 citations4 upvotesRead →HiL-Bench (Human-in-Loop Benchmark): Do Agents Know When to Ask for Help?Frontier AI agents struggle with judgment calls about when to seek help, leading to poor performance on incomplete or ambiguous tasks despite having sufficient capabilities.Scale AI28 citations4 upvotesRead →
Other multimodal and robotics papers
TopicSegment AnythingA promptable model and a dataset of over a billion masks that cut out any object in any image.
Meta16.8k citations6 upvotesRead →BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language ModelsBLIP-2 efficiently pre-trains vision-language models using off-the-shelf frozen encoders and decoders, achieving state-of-the-art performance with fewer parameters.
Salesforce9,805 citations3 upvotesRead →BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and GenerationBLIP, a Vision-Language Pre-training framework, improves performance across both understanding and generation tasks by bootstrapping captions from noisy web data, achieving state-of-the-art results on image-text retrieval, image captioning, and VQA, and showing strong generalization to video-language tasks.Salesforce7,655 citations5 upvotesRead →GPT-4o System CardGPT-4o is an omnimodal autoregressive model trained to handle text, audio, image, and video inputs, offering high-performance outputs across these modalities, with particular strengths in vision and audio.
OpenAI5,388 citations88 upvotesRead →SAM 3: Segment Anything with ConceptsSegment Anything Model 3 achieves state-of-the-art performance in promptable concept segmentation and tracking by leveraging a unified model architecture with decoupled recognition and localization.Meta1,466 citations138 upvotesRead →DeepSeek-VL: Towards Real-World Vision-Language UnderstandingDeepSeek-VL is an open-source vision-language model that achieves state-of-the-art performance in real-world applications by combining a hybrid vision encoder with effective pretraining strategies to preserve language model capabilities.
DeepSeek939 citations49 upvotesRead →
About this paper
- Venue
- arXiv.org
- Citations
- 3, 0 influential · Semantic Scholar
- Upvotes
- 6 · Hugging Face
- Lab
- Scale AI · on Companies · on Acquisitions · on awards · on breaches · on Attested · on Rounds · on Downtime · on labs · on Leaders · on marketplaces · on Allied · on Paydays · on quotes · on salaries · on Nines · on socials · on startups · on terms · on Titlewave
Changes
Citations rose from 2 to 3.
Citations rose from 1 to 2.
Hugging Face upvotes rose from 4 to 6.
A first count of 0 influential citations.
A first count of 1 citations.
Added to the list.