- Team of Thoughts: Efficient Test-time Scaling of Agentic Systems through Orchestrated Tool Calling
Jeffrey T. H. Wong, Zixi Zhang, Junyi Liu, Yiren Zhao · Feb 18, 2026 · Citations: 0
Expert Verification
Existing Multi-Agent Systems (MAS) typically rely on static, homogeneous model configurations, limiting their ability to exploit the distinct strengths of differently post-trained models.
- Step 3.5 Flash: Open Frontier-Level Intelligence with 11B Active Parameters
Ailin Huang, Ang Li, Aobo Kong, Bin Wang, Binxing Jiao · Feb 11, 2026 · Citations: 0
Pairwise Preference
We introduce Step 3.5 Flash, a sparse Mixture-of-Experts (MoE) model that bridges frontier-level agentic intelligence and computational efficiency.
- $V_1$: Unifying Generation and Self-Verification for Parallel Reasoners
Harman Singh, Xiuyu Li, Kusha Sareen, Monishwaran Maheswaran, Sijun Tan · Mar 4, 2026 · Citations: 0
Pairwise Preference Automatic Metrics
On code generation (LiveCodeBench, CodeContests, SWE-Bench) and math reasoning (AIME, HMMT) benchmarks, V_1-Infer improves Pass@1 by up to 10% over pointwise verification and outperforms recent test-time scaling methods while being…
- Duel-Evolve: Reward-Free Test-Time Scaling via LLM Self-Preferences
Sweta Karlekar, Carolina Zheng, Magnus Saebo, Nicolas Beltran-Velez, Shuyang Yu · Feb 25, 2026 · Citations: 0
Pairwise Preference Automatic Metrics
Building on this observation, we introduce Duel-Evolve, an evolutionary optimization algorithm that replaces external scalar rewards with pairwise preferences elicited from the same LLM used to generate candidates.
- Think$^{2}$: Grounded Metacognitive Reasoning in Large Language Models
Abraham Paul Elenjical, Vivek Hruday Kavuri, Vasudeva Varma · Feb 21, 2026 · Citations: 0
Pairwise Preference Human Eval
We introduce a psychologically grounded metacognitive framework that operationalizes Ann Brown's regulatory cycle (Planning, Monitoring, and Evaluation) as a structured prompting architecture, and study its integration within a lightweight…
- EasyAnimate: High-Performance Video Generation Framework with Hybrid Windows Attention and Reward Backpropagation
Jiaqi Xu, Kunzhe Huang, Xinyi Zou, Yunkuo Chen, Bo Liu · May 29, 2024 · Citations: 0
Pairwise Preference Human Eval
To enhance video generation quality, we optimize EasyAnimate using reward backpropagation to better align with human preferences.
- RLShield: Practical Multi-Agent RL for Financial Cyber Defense with Attack-Surface MDPs and Real-Time Response Orchestration
Srikumar Nayak · Feb 26, 2026 · Citations: 0
Automatic Metrics
This paper proposes RLShield, a practical multi-agent RL pipeline for financial cyber defense.
- The Tool Decathlon: Benchmarking Language Agents for Diverse, Realistic, and Long-Horizon Task Execution
Junlong Li, Wenshuo Zhao, Jian Zhao, Weihao Zeng, Haoze Wu · Oct 29, 2025 · Citations: 0
Automatic Metrics
To address this gap, we introduce the Tool Decathlon (dubbed as Toolathlon), a benchmark for language agents offering diverse Apps and tools, realistic environment setup, and reliable execution-based evaluation.
- Critique-Coder: Enhancing Coder Models by Critique Reinforcement Learning
Chi Ruan, Dongfu Jiang, Yubo Wang, Wenhu Chen · Sep 26, 2025 · Citations: 0
Critique Edit
We fine-tune multiple models (Critique-Coder) and evaluate them on different benchmarks to show their advantages over RL-only models.
- Distribution-Aware Companding Quantization of Large Language Models
Athul Radhakrishnan, Siddhant Mohan, Mahima Sachdeva · Feb 27, 2026 · Citations: 0