Update benchmark docs and parser question types

fix: use tqdm.write() for question result lines

fix: add MCQ_MATCHING and INTEGER_2 to prompt templates

chore: track results/ in git, remove dead comment

fix: correct JEE Advanced marking scheme (3 bugs)

data: add JEE Advanced 2026 (102 questions, P1+P2)

ux: sticky progress bar and live cost tracking

ux: cleaner progress bars with live score line

perf: filter records before Dataset.from_list to avoid decoding images

deps: upgrade huggingface-hub to 1.15.0 (adds Xet storage support)

charts: declutter cost-vs-accuracy plot

charts: register Gemma 4 31B IT display name

results: Gemma 4 31B IT on NEET 2026 — 700/720 (97.2%)

charts: register Gemini 3.1 Flash Lite display name

results: Gemini 3.1 Flash Lite on NEET 2026 — 700/720 (97.2%)

config: add Gemini 3.1 Flash Lite

results: Kimi K2.5 on NEET 2026 — 705/720 (97.9%)

results: Mistral Medium 3.5 on NEET 2026 — 402/720 (55.8%)

config: add Mistral Medium 3.5, Kimi K2.5, Gemma 4 31B

results: Claude Opus 4.7 on NEET 2026 — 605/720 (84.0%)

fix(charts): readable cost axis and label spacing on cost-vs-accuracy

scripts: add Grok 4.3 display name and color to chart generator

results: Grok 4.3 on NEET 2026 — 696/720 (96.7%)

config: add x-ai/grok-4.3 to model list

fix(charts): point watermark to huggingface.co dataset URL

results: GPT-5.4 on NEET 2026 — 497/720 (69.0%)

results: GPT-5.5 on NEET 2026 — 710/720 (98.6%)

scripts: add NEET 2026 chart generator

config: add openai/gpt-5.4 to model list

results: Qwen3-VL 235B Thinking on NEET 2026 — 685/720 (95.1%)

scripts: add patch_one_question.py for re-running single failed questions

results: Claude Sonnet 4.6 on NEET 2026 — 670/720 (93.1%)

results: Claude Haiku 4.5 on NEET 2026 — 516/720 (71.7%)

results: GLM-4.6V on NEET 2026 — 645/720 (89.6%)

config: add anthropic/claude-haiku-4.5 to model list

fix: tolerate provider-specific wrapper tokens and bare answers

feat: extend reasoning_effort to qwen/* and z-ai/*; add Qwen3-VL and GLM-4.6V

results: gemini-3.1-pro-preview on NEET 2026 — 710/720 (178/180)

docs: add NEET 2026 to README dataset coverage (578 → 758 questions)

results: gemini-3-flash-preview on NEET 2026 — 715/720 (179/180)

feat: sort predictions.jsonl and summary.jsonl by question_id at run end

feat: enable thinking effort for Google Gemini models (default high)

data: add NEET 2026 (paper code 13) — 180 questions

feat: enable extended thinking for Claude models (anthropic/*)

config: remove o3, keep gpt-5.5

config: increase max_concurrent_requests to 8

config: raise max_tokens to 32000 and request_timeout to 600s for thinking models

docs: update README for concurrent calls, summary.jsonl fields, partial-credit indicator

fix: write exam_name/exam_year to summary.jsonl; accumulate reprompt cost+tokens

feat: concurrent API calls via ThreadPoolExecutor (default 4 workers)