7 papers
TEX: Test-Time Scaling Testing Agents via Execution-based Cross-Validation
Akash Gokul, Srijan Bansal, Yingbo Zhou +1
Test-case generation is critical but remains challenging for language models. Existing test-time scaling methods either isolate candidates or aggregate traces, which do not scale t…
Scaled Companion Linearizations for Coefficientwise Backward Stability
Javier Pérez
A central goal in solving a polynomial eigenvalue problem is to compute eigenpairs that are exact for a nearby polynomial, with each coefficient perturbation bounded by a modest mu…
Understanding the Synergy between SFT, RLVR, and OPD in LLM Post-Training
Emre Can Acikgoz, Yang Li, Zeyu Leo Liu +4
Modern LLM post-training composes supervised fine-tuning (SFT), reinforcement learning with verifiable rewards (RLVR), and on-policy distillation (OPD) into multi-stage pipelines,…
Procedural Memory Distillation: Online Reflection for Self-Improving Language Models
Ye Liu, Srijan Bansal, Bo Pang +6
Reinforcement learning with verifiable rewards (RLVR), along with recent selfdistillation variants such as SDPO, evaluates each rollout against a verifier and updates the policy fr…
VIBEPASS: Can Vibe Coders Really Pass the Vibe Check?
Srijan Bansal, Jiao Fangkai, Yilun Zhou +3
As Large Language Models shift the programming toward human-guided ''vibe coding'', agentic coding tools increasingly rely on models to self-diagnose and repair their own subtle fa…
Self-Abstraction from Grounded Experience for Plan-Guided Policy Refinement
Hiroaki Hayashi, Bo Pang, Wenting Zhao +6
Large language model (LLM) based agents are increasingly used to tackle software engineering tasks that require multi-step reasoning and code modification, demonstrating promising…
Does Context Matter? ContextualJudgeBench for Evaluating LLM-based Judges in Contextual Settings
Austin Xu, Srijan Bansal, Yifei Ming +2
The large language model (LLM)-as-judge paradigm has been used to meet the demand for a cheap, reliable, and fast evaluation of model outputs during AI system development and post-…